TensorflowJobs

...catalogue, smart search, personalised product feeds, in-app marketing tools, cart, checkout, order tracking and an admin dashboard. • Map AI touchpoints such as image-based product recognition, dynamic pricing, recommendation engines and automated customer-service chat. • Recommend the full tech stack: mobile frameworks (e.g. Flutter, React Native or native), backend, database, AI/ML services (TensorFlow Lite, Core ML, Amazon Personalize, etc.) and third-party APIs for payments, shipping and analytics. • Lay out an annotated wireframe or low-fidelity screen flow that illustrates how users move from discovery to purchase. • Provide a phased development timeline broken into logical sprints with expected deliverables, QA tasks and app-store submission ste...

...consumer-goods products in high-resolution images captured on our manufacturing line. The goal is to distinguish each finished item from background equipment, operators, and any other visual noise so that we can feed the detections into our downstream QA and inventory systems. You will start with raw JPEGs taken under factory lighting, then design, train, and validate an object-detection model—PyTorch or TensorFlow is fine—capable of achieving consistent, real-time performance on an NVIDIA GPU. If you prefer a different framework, let me know why; I’m flexible as long as the final solution is easy for my engineering team to maintain. Deliverables • Annotated sample dataset (in COCO or YOLO format) • Trained detection model with weights and versio...

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...annotation workflow for a sizeable corpus of text data, then feed that clean, well-labeled material back into the training loop. You should already have hands-on experience setting up annotation guidelines, managing annotators or automation tools, and integrating the resulting labels into a machine-learning or deep-learning pipeline. Familiarity with popular NLP libraries (spaCy, Hugging Face, TensorFlow, PyTorch, etc.) will be essential, as the final objective is to boost downstream model performance by improving label quality and consistency. Deliverables • A documented text-annotation schema aligned with task objectives • A functioning annotation pipeline (can be human-in-the-loop, semi-automated, or fully automated—whichever you recommend and justify) ...

...predictive or generative solutions Integrate AI models into existing systems and workflows Optimize models for performance, scalability, and accuracy Collaborate with stakeholders to understand business needs and translate them into technical solutions Requirements: Proven experience as an AI Engineer, Machine Learning Engineer, or similar role Strong knowledge of Python and libraries such as TensorFlow, PyTorch, or scikit-learn Experience with APIs and model deployment (Docker, Kubernetes, or cloud platforms like AWS/Azure/GCP) Familiarity with LLMs, NLP, or computer vision is a plus Ability to communicate clearly and work independently Nice to Have: Experience with MLOps pipelines Background in data engineering or DevOps Experience integrating AI into production systems Pr...

...iOS et Android publiée sur les stores (App Store + Google Play) dès la première version (MVP), multilingue (10 langues), avec : IA adaptative (niveau, rythme, difficulté) Jeux éducatifs type Montessori Module AAC (pictogrammes + TTS) Mode offline partiel (~60%) Tableau de bord + export PDF Accessibilité (RGPD, COPPA) Stack technique obligatoire Flutter (frontend) Firebase (backend) Python + TensorFlow Lite (IA) Stripe + In-App Purchases (paiements mobiles) Livrables attendus UI/UX Figma complète MVP fonctionnel Intégration IA (v1) Publication sur App Store et Google Play (obligatoire) Comptes développeur configurés (ou accompagnement) Documentation technique complète Budget & conditions Merci de ...

...other report. The module has to do three concrete things for every run: • Calculate current inventory levels for each SKU in real time. • Work out key supply-chain metrics such as reorder point, days of cover and in-transit quantities. • Produce an accurate stock valuation that respects my weighted-average method already configured in Tally. I do not mind whether you build the model in TensorFlow, PyTorch or another modern framework—use whatever lets you finish quickly and keep maintenance simple. A neat Python script with an .exe wrapper, or a light web service that Tally can call through ODBC or REST, would both be fine as long as the end result lands in Tally every day without manual intervention. Acceptance criteria • A single-click (or sc...

...carried by the drone (Jetson Xavier NX or similar) or stream efficiently to a ground server if you have a smarter approach. • Expose a clean API that returns the recognised ID, confidence score, and a yes/no flag my flight-control software can act on. • Allow me to enrol new authorised faces quickly—either by uploading images or shooting a short video clip. Deliverables 1. Trained model (TensorFlow, PyTorch, or ONNX) with all weights and source code. 2. Companion-computer integration script and clear step-by-step setup guide. 3. Demo footage (or a live test, if you prefer) proving ≥95 % accuracy with latency under 300 ms. 4. Concise documentation covering hardware requirements, installation, and how to maintain or update the face database. If you&rs...

...replies accurately in real time. You will own the entire NLP pipeline—from preparing the data right through to deploying a trained model that plugs cleanly into my C#/ASP.NET Core back end. I’ll supply domain-specific dialogue examples and hosting. Your job is to choose or fine-tune the appropriate model, train and evaluate it, and expose a lightweight API that my front end can call. , TensorFlow, or Azure Cognitive Services are all acceptable as long as the final solution remains self-contained in the Microsoft stack and is easy for me to maintain. Deliverables • Fully commented .NET source code for the chatbot service • Trained model files and any training scripts • Step-by-step deployment and configuration guide • Brief test plan showi...

...model behavior based on detected condition Re-trains or fine-tunes on recent data periodically 4. Intraday Focus Operates on 1min / 5min / 15min timeframes Signals generated in real time during market hours 5. Output / Dashboard Simple UI showing current signal, confidence score, market regime Alert via Telegram or email when signal triggers Tech Stack Suggestion Python (core) scikit-learn / TensorFlow / PyTorch (ML) CCXT library (crypto exchange connectivity) Streamlit (quick dashboard) PostgreSQL (data storage) Important Notes for Coder No predefined strategy — system must learn from data Must handle both crypto (24/7) and commodity markets (Gold) Risk management module needed: stop-loss, position sizing suggestions Backtesting module essential before going live...

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...backgrounds, and even finger counts may vary. The goal is to turn this dataset into a practical analysis tool that can: • calculate the flexion/extension angle at every finger joint in each image • flag when a finger or phalanx is completely absent so that it can be recorded automatically I expect you will combine classical computer-vision preprocessing with a deep-learning model (PyTorch or TensorFlow are fine) and possibly leverage pose-estimation libraries such as MediaPipe or OpenCV for landmark detection. Accuracy matters more than perfection in lighting or background, so robust data-augmentation and domain-adaptation techniques will be key. Phase 1 Train and validate a model that ingests a single hand photograph and returns a JSON or CSV containing joint ...

...photos and I need an AI mechanism that can automatically locate every tooth in each image, assign the correct FDI or Universal numbering, and clearly classify each tooth type (incisor, canine, premolar, molar, wisdom). You are free to decide whether a pre-trained or custom-built model is best; accuracy and speed matter more to me than the underlying brand of framework. Python with PyTorch or TensorFlow, OpenCV for preprocessing, and a clean REST or CLI inference interface would suit my workflow, but if you have a more elegant stack, I’m open. Key deliverables • A trained model capable of processing new intraoral 3d scans and returning JSON with tooth positions, numbers and classes. • Lightweight script or API endpoint to run the model locally or on a sma...

...ethical data handling, and an engaging personality that feels genuinely helpful rather than gimmicky. Here’s how I picture the collaboration: • You start by reviewing my initial concept notes, asking the right discovery questions, and proposing architecture options (native Swift/Kotlin, Flutter, React Native, or another stack) along with any AI frameworks you find appropriate—OpenAI APIs, TensorFlow Lite, Core ML, etc. • We agree on an MVP scope, sketch wireframes, and iterate on a clickable prototype so we can validate “lovability” early. • You then build the backend and mobile front end, integrate the chosen AI models, and fine-tune prompts or training data until the experience feels natural. • Finally, you package everyth...

...CCTV style feeds (fixed street-level cameras). • No real-time push notifications are required—the result can appear once processing is finished. I will rely on you to select or curate a robust, publicly available dataset (or a combination of datasets) that truly represents urban crash scenarios, then fine-tune an architecture such as YOLOv8, Faster R-CNN, or another proven model in PyTorch/TensorFlow. Accuracy and speed matter equally; anything under a few seconds for a one-minute clip on a modern GPU is ideal. Deliverables • Trained model files and all preprocessing scripts • Lightweight desktop or web demo (Python + OpenCV/Streamlit/Flask—your call) mirroring the UI flow above • At least three short demo videos that clearly show LOW, ...

...analytics model once the core site is live. If you work best with React, Vue, or another modern framework, that’s fine; I’m flexible as long as the result is responsive and maintainable. On the server side, I expect clean, well-documented code, REST or GraphQL endpoints, and a data schema that supports model training and inference later on. When it’s time to integrate the ML piece, Python with TensorFlow or PyTorch is totally acceptable, but again, I’m open to recommendations if you have a more efficient pipeline in mind. Deliverables will include: • A complete, deploy-ready web application with user authentication and the core pages wired up • An API layer prepared to feed data into—and receive predictions from—the machine-learn...

...Real-time dashboards & MIS reports • Automated SMS, Email & In-app alerts • Escalation matrix (3 levels) --- REQUIRED SKILLS Full Stack: • React.js or (Frontend) • Node.js / Python (Backend) • REST API development • MySQL / PostgreSQL Also Front-end design AI / ML: • Production scheduling algorithms • Demand forecasting (time-series) • Predictive delay alerts • Python (scikit-learn / TensorFlow / PyTorch) Integration: • Tally ERP API / ODBC / TDL experience (preferred) • Third-party SMS & Email API integration --- WHAT WE EXPECT • Work closely with our team and communicate professionally with stakeholders • Deliver clean, documented, scalable code • Participate in client calls when ne...

...additional brokers can be added with minimal code changes. Self-improvement Beyond static strategies, the system should evaluate its own performance, retrain when accuracy drops, and log insights for me to review. Reinforcement-learning or similar approaches are welcome as long as you can justify them in documentation. Core tech I expect to see mentioned naturally in your approach includes Python, TensorFlow or PyTorch for modelling, an NLP layer (e.g., OpenAI GPT, Rasa) for the chat component, and a robust back-testing framework. Deliverables • Fully functional trading engine with live and paper modes • Conversational module (casual & friendly tone) accessible via web dashboard or chat widget • Self-improving training pipeline with performance metri...

...pain-level monitoring through self-reported scales (no wearables in the first release). • Visual progress tracking that highlights correlations between pain scores and performance. I’m flexible on the final tech stack—React Native, Flutter, native iOS/Android, or a responsive web front end are all acceptable as long as the user experience stays fluid. A lightweight Python or Node.js backend running TensorFlow, PyTorch, or a comparable ML library would suit the recommendation engine, but I’m open to your proposal. Deliverables 1. Fully functional MVP with user onboarding, daily pain check-ins, dynamic workout generator, and progress dashboard. 2. Clean, well-documented code repo plus brief setup guide. 3. Post-launch support window to fix critical ...

...(red = metal, blue = glass, grey = concrete, orange = wood, green = plastic). • The charts have to highlight the mean and standard deviation for every variable so the artists immediately see the “typical” trajectory as well as the natural spread. Other metrics such as percentiles or min/max can stay in the background; we will only display them later if the director asks. • A short Python/TensorFlow (or PyTorch) pipeline is preferred so we can regenerate results when the blast parameters change. Feel free to leverage NumPy, Pandas and Plotly or Matplotlib for plotting—whatever keeps the workflow light and editable. • Final delivery should include the source code, a reproducible notebook, the generated CSV/JSON of raw predictions and the rende...

I need a rock-solid, real-time player tracking module for football matches that guarantees the ID assigned to each athlete at kick-off never changes until the final whistle. Right now, our OpenCV–TensorFlow–YOLO pipeline sometimes swaps or loses IDs when athletes overlap, leave the frame briefly, or the camera angle shifts, and that ruins every speed, distance, position, and heat-map metric we generate. Key requirements • Sport: football. • Camera setup: five or more synchronized feeds. • Existing stack: OpenCV, TensorFlow, YOLO – your solution must plug into this environment. What I expect 1. A multi-object tracker with integrated re-identification that preserves the same unique ID through occlusion, crossings, short disappearances, or ...

...tables where they genuinely aid clarity, and cite all sources meticulously. I accept either APA 7th or IEEE style—pick one and stay consistent. Deliverables 1. A polished 3 000–5 000-word report in editable Word (or LaTeX PDF) plus a clean PDF. 2. All reference entries and in-text citations formatted correctly. 3. A short appendix detailing any datasets, code repos, or tools referenced (TensorFlow, PyTorch, OpenCV, etc.). 4. Turnitin similarity report and confirmation that the text passes common AI-content detectors (GPTZero, ). Acceptance Criteria • Every statistic is traceable to a cited, peer-reviewed source. • Comparative discussion is data-driven, not anecdotal. • Language flows naturally and survives AI-detection checks. • F...

...tables where they genuinely aid clarity, and cite all sources meticulously. I accept either APA 7th or IEEE style—pick one and stay consistent. Deliverables 1. A polished 3 000–5 000-word report in editable Word (or LaTeX PDF) plus a clean PDF. 2. All reference entries and in-text citations formatted correctly. 3. A short appendix detailing any datasets, code repos, or tools referenced (TensorFlow, PyTorch, OpenCV, etc.). 4. Turnitin similarity report and confirmation that the text passes common AI-content detectors (GPTZero, ). Acceptance Criteria • Every statistic is traceable to a cited, peer-reviewed source. • Comparative discussion is data-driven, not anecdotal. • Language flows naturally and survives AI-detection checks. • F...

...that reliably turns an input photo into a cartoon-style portrait with moderate detail. The focus is squarely on portraits, not landscapes or abstract work, and I’m after a playful yet recognisable look—clean lines, balanced shading and colour, no hyper-realistic textures. You’re welcome to fine-tune Stable Diffusion, train a lightweight GAN, or build a custom pipeline in Python using PyTorch or TensorFlow, as long as the result runs locally (GPU) and can be triggered by a simple command-line or minimal web interface. I’ll supply a handful of sample headshots for calibration; please keep facial proportions faithful while still achieving that classic cartoon charm. Deliverables: • Trained model files and any checkpoints • Inference script or mi...

I need a compact, well-structured script that ingests a 2D image and returns a high-quality .glb file in one pass, with no noticeable loss of fidelity. Speed is critical; the final tool should feel almost instantaneous when run on a modern desktop. Because I have no fixed preference for specific libraries, feel free to choose whatever stack best balances performance and quality—OpenCV, TensorFlow, or any other framework you’re confident will get the job done quickly and cleanly. What matters most is that the resulting geometry, textures, and materials in the .glb look crisp and faithful to the source image. Deliverables • Source code with clear inline comments • A straightforward README explaining environment setup, usage, and any dependencies • A ...

...flagging, I also want deeper malware analysis so I can review payload characteristics and produce short forensic reports. Required deliverables • Clean, well-documented Python scripts covering – malware analysis (static and/or dynamic) – real-time malware monitoring across the network – fully automated reaction once a threat is confirmed • A lightweight training or inference model (TensorFlow, PyTorch or scikit-learn are all fine) integrated into the scripts • Configuration file(s) so thresholds, network taps and response actions can be adjusted easily • A brief README with setup instructions and an example dataset for validation Acceptance criteria The system must detect and react to known and previously unseen malwar...

...plan to streamline several internal workflows with machine-learning powered automations and, in parallel, launch a tailored chatbot that reflects my brand voice. The engagement is split into two connected tracks: 1. Smart automation • Map current data flows, then design and deploy Python-based pipelines that ingest data from my CRM and analytics dashboards. • Train and tune models (TensorFlow / scikit-learn preferred) to surface predictive insights—think churn risk and high-value lead scoring—served through a lightweight API so the business team can consume results in real time. 2. Custom chatbot • Build a conversational agent (Rasa, Dialogflow, or a comparable LLM stack) able to switch context between customer support queries and basic...

I'm seeking an AI/ML programmer to develop an image classification model specifically for fingerprint recognition. Key requirements include: - Expertise in image recognition and classification - Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) - Strong background in handling and processing image datasets - Knowledge of security and privacy considerations in biometric data Ideal candidates will have a proven track record in similar projects and the ability to deliver accurate and efficient models.

...someone replies, likes, or when it is time for their next practice. • Admin console for moderating content and managing reported posts. I’m open to advice on the tech stack, but I’ll lean toward a single codebase approach (React Native, Flutter, or similar) paired with a scalable backend (Firebase, Supabase, or Node/Express + PostgreSQL). If you have a preferred ML library for pose recognition—TensorFlow Lite, MediaPipe, etc.—let me know. Deliverables will be: 1. Clickable prototype for approval of UX flow 2. Production-ready iOS & Android builds 3. Source code in a private repo with clear README and build instructions 4. Brief hand-over call or video walk-through I’ll handle copy and imagery; you focus on architecture, design, ...

...other research features. - Customize the solution according to the client’s specific needs. Key Requirements: 1. Technical Skills (Required): - Strong experience with Google BigQuery (SQL, data modeling, optimized querying, data ingestion, and BigQuery ML). - Practical experience building and deploying Machine Learning models for time-series or financial data (using Python, scikit-learn, TensorFlow, PyTorch, or BigQuery ML). - Proficiency in Python for data processing and ML pipelines. - Ability to work with large datasets and build efficient search/analytics systems. 2. Financial Knowledge: - Basic to intermediate understanding of bonds and fixed-income markets is preferred (bond pricing, yields, etc.). - You should be comfortable working with bond-rel...

...tailors content or products to each visitor, and image-recognition functionality for richer visual search and tagging. Because day-to-day collaboration is important to me, I strongly prefer a Bangalore-based developer who can drop in for an occasional discussion or rapid demo. You should be comfortable choosing the right mix of frameworks—think React or Vue on the front end, Node/Python with TensorFlow or similar for the AI services, and a scalable database such as PostgreSQL or MongoDB—so long as the result is fast, secure and easy for my team to maintain. Key deliverables • Fully responsive, production-ready website with integrated chatbot, recommendation engine and image-recognition modules • Admin panel to manage content, datasets and AI tuning param...

...for SMS, call logs, microphone, notification access and accessibility API where needed • Continuous background collection without draining battery (WorkManager / JobScheduler best practices) • Local encryption of raw data and inference results; nothing readable should leave the device unless explicitly routed through a secure API endpoint I configure • Modular AI layer: you may integrate TensorFlow Lite, OpenAI APIs or a comparable model, provided it can run entity extraction and intent detection reliably • Minimum target SDK 31; written in Kotlin with clean architecture so I can extend it later Deliverables 1. Signed APK plus source code in a private Git repo 2. Brief setup guide outlining required API keys and permission steps 3. README desc...

...force-push ke main. • Menulis test secara pragmatis — critical path ter-cover, bukan pura-pura 100% coverage. • Bisa membaca dan refactor codebase yang belum familiar. Nilai tambah yang kuat • Pengalaman media pipeline: image processing, thumbnail, CDN delivery, video transcoding. • Integrasi model ML (bukan training): memanggil model face recognition lewat API atau menjalankan inference dengan ONNX/TensorFlow Serving. Pemahaman tentang embedding dan vector similarity search adalah nilai plus. • Background job system: queue (BullMQ, Celery, SQS), cron job, async workflow. • Pengalaman mobile-web atau React Native. • Pola multi-tenancy. Cara melamar Kirimkan: 1. Catatan singkat mengapa peran ini spesifik buatmu (bukan cover letter generik)...

...and external device connectivity. -Vehicle number plate recognition / LPR systems. -Cloud architecture, DevOps, and deployment pipelines. -QA and testing for real-time and AI-driven systems. Preferred Technical Stack Experience Experience with the following technologies will be highly valuable: or similar dashboard frameworks. , Python, or similar backend stacks. -OpenCV, TensorFlow, PyTorch, YOLO, FaceNet, DeepFace, EasyOCR, or OpenALPR. -FFmpeg, WebRTC, or GStreamer for video processing. -Docker, Kubernetes, CI/CD, and cloud deployment. -Secure authentication, RBAC, logging, and scalable system architecture. Who Should Apply: We are looking for freelancers who can contribute to a serious, real-world, production-grade platform. This project requires people who understand

...with numerical features, and return forward-looking insights. In practice that means designing an architecture able to embed and fuse both modalities, training it on my mixed dataset, and validating that the model can reliably forecast the target variables we care about. You will take me from data preprocessing through to an inference-ready checkpoint. I expect clean Python code (PyTorch or TensorFlow), sensible use of the Transformers or similar libraries, and a clear explanation of why each modelling choice was made. Please include evaluation notebooks that show the lift over conventional baselines and provide an API-style script so I can drop the model straight into production once testing is complete. Deliverables • End-to-end training pipeline with documented source...

...layering in additional modules such as automated email campaigns, an analytics dashboard or even a chatbot assistant, provided they plug into the same ML backbone without bloating the codebase. Feel free to suggest alternatives if you have a better architectural approach. Tech stack is flexible as long as you choose tools proven for production-grade AI apps (e.g., Python, FastAPI, Node, React, TensorFlow/PyTorch, PostgreSQL). Code needs to be well-documented and checked into a private Git repository with clear setup instructions so my in-house team can continue iterating after hand-off. Acceptance criteria: 1. The platform trains and deploys ML models on real or sample legal-marketing data and surfaces actionable recommendations. 2. A user with no coding background can crea...

...Extract relevant entities (names, dates, IDs, product references, etc.) from the same messages. You will own the entire machine-learning workflow. That means cleaning and exploring the raw email text, crafting useful features, training and tuning your models, and packaging the final solution behind an API that I can call from our existing back-end. Python is a must, and I’m comfortable with either TensorFlow or PyTorch for the deep-learning components—use whichever lets you move fastest. Traditional techniques with Scikit-learn are welcome wherever they make sense. Because the email stream is live, the models have to run efficiently at scale and be easy to retrain when new data arrives. A clean, well-documented repo, reproducible training scripts, and a straightforw...

...climate-responsive façade control framework Expected Deliverables: Machine learning model (Python / MATLAB / suitable platform) Feature importance analysis Predictive control strategy for shading and ventilation Documentation explaining methodology and results Optional: Conceptual AI façade control system diagram Preferred Skills: Machine Learning / Artificial Intelligence Python (Scikit-learn / TensorFlow / PyTorch) or MATLAB Data analysis and predictive modeling Experience with building or façade performance data is a plus Project Type: Short-term project Timeline: Flexible (2–4 weeks preferred)...

...clear decision to the passenger-facing touchscreen. Core vision logic The heart of the project is a YOLO-based model fine-tuned on our curated luggage set. My primary goal is accurate baggage classification; precise dimensioning and weight checks come next, so the model must fuse vision, distance, and scale readings to flag oversize or overweight items. You are free to optimise in PyTorch or TensorFlow, but the final network should run locally on the kiosk and expose an optional Google Cloud endpoint for batch retraining or overflow processing. Touch-first interface The front end runs on a 15” touchscreen and must walk travellers through multilingual (English/Spanish) boarding-pass validation, a payment screen for excess fees, and a final approval printout/QR. I will ...

...centers on end-to-end model creation: cleaning and preprocessing raw text, selecting the right architecture, training, and evaluating performance against clearly defined metrics. I will supply the text dataset along with the target variable I want predicted. You will decide on the most suitable NLP approach—whether that’s classical techniques with scikit-learn or a deep-learning stack such as TensorFlow or PyTorch—document your reasoning, and implement the solution in clean, well-commented Python. Deliverables: • Reproducible code (Jupyter notebook or .py files) with setup instructions • A trained model saved in a shareable format • Evaluation report outlining methodology, key metrics, strengths, and limitations • Brief hand-off sessi...

...and interpretability both matter. Here’s what I need from you: • A brief data-exploration notebook that highlights key correlations, missing-value handling, and basic visuals. • Feature engineering tailored to the data’s domain (scaling, encoding, derived metrics, etc.). • At least two supervised algorithms (for example, Gradient Boosting and Random Forest in scikit-learn, or an XGBoost/TensorFlow alternative) trained, cross-validated, and benchmarked. • A concise performance comparison using appropriate regression/classification metrics—whichever fits once you see the target variable. • The final, best-performing model saved in a reusable format (pickle/joblib or SavedModel). • A short read-me that explains: setup step...

...and interpretability both matter. Here’s what I need from you: • A brief data-exploration notebook that highlights key correlations, missing-value handling, and basic visuals. • Feature engineering tailored to the data’s domain (scaling, encoding, derived metrics, etc.). • At least two supervised algorithms (for example, Gradient Boosting and Random Forest in scikit-learn, or an XGBoost/TensorFlow alternative) trained, cross-validated, and benchmarked. • A concise performance comparison using appropriate regression/classification metrics—whichever fits once you see the target variable. • The final, best-performing model saved in a reusable format (pickle/joblib or SavedModel). • A short read-me that explains: setup step...

...(vector analysis). 3. State Transition: The algorithm must seamlessly transition from "Bulge Tracking" (closed eyes) to standard "Pupil/Iris Tracking" (open eyes) within the same 30-second video clip. 4. Mobile Optimization: The final module must be lightweight and optimized for real-time or near-real-time performance on iOS and Android devices. Candidate Profile • Expertise in OpenCV, MediaPipe, TensorFlow Lite, or CoreML. • Proven track record in Image Processing or Eye-Tracking projects. • Strong background in Motion Analysis and extracting signals from noisy video data. • Experience in delivering code ready for mobile integration. Application Instructions Please include the following in your proposal: • Examples of previous work in...

...project centres on building a production-ready medical image -classification pipeline that leverages modern deep-learning techniques. I have a labelled dataset and need end-to-end code that ingests the text, handles cleaning and tokenisation, and trains an accurate classifier. Python is the preferred language; The preprocessing must involve Quantum computing techniques using Pennylane. PyTorch, TensorFlow or another mainstream framework is fine as long as the solution is reproducible and easy to extend. Key deliverables: • Well-commented source code (data loading, model, training loop, evaluation) • Clear instructions to run training on a fresh machine (README or notebook) • Metrics report showing accuracy, precision, recall and F1 on a held-out set • ...

...(Finacle, Oracle, Temenos, or similar) │ ├── Developed reconciliation engines for payments │ ├── Implemented fraud detection systems │ └── Deployed systems in regulated environments (finance, healthcare, government) NICE TO HAVE: ├── Experience with Africa's Talking SMS gateway ├── Knowledge of Levenshtein distance or fuzzy matching algorithms ├── Experience with ML model deployment (TensorFlow, PyTorch) ├── Previous work with microservices architecture ├── Experience with Elasticsearch, Kibana (ELK stack) ├── Familiarity with banking regulations (data protection, PCI-DSS) └── Existing relationships with telco or bank technical teams WHAT WE ALREADY HAVE (The Assets You'll Integrate) We are NOT starting from scratch. The following assets are already bui...

suspicious activity detection using deep learning # Features Real-Time Detection: Monitors live camera feeds and detects suspicious activities instantly. Multi-Class Detection: Classifies activities such as hara...fighting, vandalism, and abuse. Alert System: Sends real-time notifications to authorities upon detecting suspicious activities. Dataset-Based Training: Trained on UCF-Crime, AVENUE Video Dataset, and Violent-Flows for high accuracy. Technologies Used YOLOv8: For real-time object and people detection. CNN-LSTM: For recognizing and classifying human activities. Deep Learning Frameworks: TensorFlow, PyTorch. Backend: Flask/Django (replace with your backend framework). Frontend: Minimalistic web interface for real-time monitoring. Alert System: Email (integrated w...

...lighting at the doorway • Automatic in/out logic that prevents double entries when someone lingers near the camera • Admin dashboard with search, manual override and CSV/XLS export • Installation guide plus brief training so I can manage enrolments myself • Source code or licence details, and clear instructions for future camera or user expansion Feel free to use OpenCV, DeepFace, TensorFlow, AWS Rekognition, or another proven toolset—just explain the choice and any recurring costs. I will supply the RTSP stream from the entrance camera and can provision a small Windows or Linux box on-site if you recommend an on-prem edge device. Once everything is running smoothly and the test group’s times are logging correctly for a full week, I&r...

...must be available both as a responsive web application and as native or cross-platform mobile apps, all drawing from a single codebase whenever practical to streamline future maintenance. Core expectations • Modern, engaging UI/UX that feels consistent across web, iOS and Android. • A secure, multi-tenant architecture so each school’s data remains isolated. • An AI layer (think Python, TensorFlow/-Lite, or similar) that plugs into the learning workflow—for example adaptive content or real-time feedback—without locking us into a specific vendor. • Real-time sync between devices, even on spotty school Wi-Fi, and offline caching for mobile. • Admin dashboard with role-based access, permissions and exportable analytics. • C...

...fast delivery (within 24 hours) - Long-term work possible if successful Scope of Work: - Diagnose deep learning pipeline issues - Fix model execution errors - Debug training / inference workflow - Resolve dependency or environment conflicts - Optimize pipeline stability - Ensure end-to-end execution works correctly - Provide brief documentation of fixes Technical Stack: - Python - PyTorch / TensorFlow - HuggingFace / Transformers - CUDA / GPU acceleration - Docker / Linux environment - API integration & Data preprocessing pipeline Requirements: - Strong experience in Deep Learning production workflows - Experience debugging complex AI pipelines - Comfortable working under urgent timelines and ability to start immediately Timeline: Start: Immediately. Expected turnaround: ...

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