Pothole & Graffiti Model Upgrade

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@AwaisChaudhry

Your search for an accomplished and skilled freelancer to upgrade your pothole and graffiti model ends here! As the founder of ZAWN Tech and with over a decade of software development experience, I can bring immense value to this project. Proficient in Computer Vision, Deep Learning, Image Processing, Machine Learning, and Neural Networks, my expertise aligns perfectly with your needs. My team at ZAWN Tech has successfully implemented Open Source systems in numerous projects making us highly adaptable to your requirements. With the addition of extra datasets that you provide, I will ensure their careful labeling/annotation is done to boost the performance and accuracy of the models. A distinguishing factor that sets me apart is our ability to tailor solutions for different weather conditions and day-night usage. This is crucial for outdoor systems like yours - and coupled with our hardware competencies using Nvidia Jetson, I guarantee unparalleled results. Having delivered successful high-stakes projects worldwide, we are accustomed to working with precision even under pressure.

@Julian29

Hello, HAVE HANDS-ON EXPERIENCE WITH SUCH PROJECT. I bring 15+ years of proven experience in computer vision and edge AI deployment, and I clearly understand your requirement. The goal is to enhance open-source detection models for pothole and graffiti recognition with high accuracy across varying lighting and weather conditions, optimized for real-time inference on NVIDIA Jetson hardware. -->> Dataset labeling & annotation (5–10k images per class) -->> Fine-tuning YOLO/Detectron-based models for day/night & weather robustness -->> Multi-camera optimization (3 streams) with real-time edge inference -->> Jetson deployment with TensorRT acceleration & performance tuning My approach would involve structured dataset preprocessing, augmentation for environmental variance, transfer learning with rigorous validation, and edge optimization (quantization/pruning) to ensure stable FPS on Jetson devices—all delivered through milestone-based iterations. I’ve previously trained and deployed real-time object detection models on embedded GPU systems, including vehicle-mounted setups, and can share concise examples in chat. I would begin with dataset audit and annotation workflow setup, then move into controlled fine-tuning and on-device benchmarking. Confident in delivering a production-ready, field-optimized detection system from training through Jetson deployment. Thanks & regards, Julian

@irsolutions

With over 10 years of web and mobile development experience, along with expertise in AI/ML, I understand the importance of upgrading your pothole and graffiti detection models for better accuracy. Your project requires additional training on open source models, especially for day-night and varied weather conditions. I have successfully worked on similar projects in the AI/ML domain, ensuring high accuracy and performance in real-world settings. My experience in implementing intelligent solutions for various industries, including FinTech and HealthTech, aligns well with the requirements of your project. I have a proven track record of delivering tailored products that meet and exceed client expectations, driving tangible results. If you are looking for a dedicated and experienced developer to take on your pothole and graffiti model upgrade project, I am here to help. Let's work together to enhance the performance and accuracy of your detection models. Feel free to reach out to discuss the details further.

@hotanloc

Hi. Client. Thanks for your posting. I am an expert AI programer with more than 5 years. I have expertise in ML/DL, and neural network, SVM, decision tree, and other all models.I I have full experiences in TensorFlow, PyTorch, Scikit-learn and other libraries. I have completed many projects such as neural style transfer, object detection, data prediceion and forecasting... I checked your proposal carefully. I can finish your task perfectly on time. Please send me your message to discuss your project detail more...I am waiting your reply now. Thanks.

@Feriver

Hello, I understand you want to upgrade pothole and graffiti detection models using open-source frameworks, optimized for day/night and varying weather, deployable on NVIDIA Jetson hardware. I have hands-on experience in computer vision, object detection, and model fine-tuning for edge devices. I will annotate your 5–10k images per class, apply data augmentation for lighting and weather variations, and fine-tune state-of-the-art object detection networks (YOLOv8, Detectron2, or similar). Training will be optimized for Jetson GPU/edge inference to ensure real-time performance with high accuracy. I will validate using precision, recall, and mAP metrics across multiple conditions. You will receive production-ready models, labeled datasets, inference scripts, and deployment instructions for Jetson, ready for integration with vehicle-mounted cameras. Clarification Questions: Are the 3 cameras fixed-angle or pan/tilt adjustable on the vehicle? Should the model detect only presence or also classify severity/size of potholes and graffiti?

@sivakumar676

─── ⚡⭐⋆☆⋆⭐⚡ ─── Hi, Client. Hope you are doing well. Annotation: I can label pothole and graffiti datasets with consistent guidelines using CVAT or Label Studio. Model training: I fine tune open source detection models and validate across day night and weather conditions. Jetson: I can export to TensorRT and test on Nvidia Jetson for stable edge inference. I am a computer vision engineer using PyTorch and YOLO for object detection. I read the full scope and this job is to annotate 5000 to 10000 images per case then improve pothole and graffiti detection for outside use across conditions. You want higher accuracy from three vehicle cameras with reliable performance on Nvidia Jetson. I will build a reproducible training and evaluation pipeline and deliver optimized models ready for deployment. Plan Collect datasets and define label schema. Annotate images for both classes with QA sampling. Fine tune models and evaluate by lighting and weather. Optimize inference and package for Jetson deployment. Best, Siva

@adisonw

Hello, I’m very interested in this project because training open-source vision models for real-world deployment on NVIDIA Jetson requires careful optimization and domain adaptation. I’ve worked with object detection models such as YOLOv5/YOLOv8, EfficientDet, and Faster R-CNN, fine-tuning them on custom datasets with domain-specific augmentation for varied lighting and weather conditions. For pothole and graffiti detection, I would begin with dataset structuring and annotation workflow using tools like CVAT or Label Studio, ensuring consistent bounding box standards. I would apply targeted data augmentation for day/night variation, motion blur, rain, shadows, and low-light conditions to improve robustness. After training and validation, I would optimize the model using TensorRT conversion and quantization to ensure efficient inference on NVIDIA Jetson hardware. Evaluation would include precision, recall, mAP metrics, and stress testing under simulated real-world scenarios. I’d like to go over a few points: Which Jetson model will be used for deployment? Do you already have partially labeled datasets or is full annotation required? I’m confident I can deliver a production-ready, optimized detection pipeline for your vehicle-mounted cameras. Thank you for considering my proposal. Adison

@Zawiya3

As a practicing data scientist with a wealth of technical and programming experience, I am well-suited to your project's demands. My proficiency in Python, C++, and C makes me an adept candidate for the job on the development side. I am also endowed with strong analytical and problem-solving skills that have led me to excel in tasks such as image processing, motion detection, and facial recognition --all highly applicable skills for training open source models for better accuracy—specifically in-classifying different types of potholes and graffiti under varied weather conditions. Additionally, my ML background espouses finding innovative ways to tackle complex situational puzzles. When it comes to this project, that quality lends itself perfectly to the labeling/annotation dynamic involved in upgrading your models. The jetson hardware and cameras you'll be using amplified my interest further as anthropomorphically designating labels on what the recordings show definitely pique my curiosity. Lastly, my deep learning skillset entails expertise in using Keras and TensorFlow which happen to be two top deep learning libraries ideal for the task at hand. With over four years of applied experience under my belt, a characteristic that sets me apart is my commitment to client satisfaction through constant communication and meeting project deadlines.

@Cumuc

Leveraging over 6 years of experience as a Desktop Application Engineer, my proficiency in C++, C#, and Java along with frameworks like MFC, Qt Widgets, and WPF are precisely what your project needs. I have honed an understanding of open-source models which will be crucial in enhancing the efficiency of the pothole and graffiti detection models. My technical prowess extends beyond languages to include multithreading, REST APIs, serial communication, and TCP/UDP - all key components for a robust and efficient solution. Past projects have seen me develop applications for industrial sensor monitoring, inventory management, medical device interfaces and more. These spanned diverse technological needs within a wide range of sectors – a testament to my adaptability and versatility. Furthermore, I'm well-versed in SQLite, MySQL, PostgreSQL - important skills that will facilitate effective data labeling/annotation in the project. Apart from my technical qualifications, I am driven by the prospect of bringing ideas to life. The opportunity to assist you in transforming this model upgrade into an exceptional real-time application is truly exciting. Let's work together in turning this vision into an impactful solution that surpasses expectations

@noursherif030

With an expansive background in computer vision, deep learning, and machine learning, I am confident that I possess the necessary skills to upgrade your pothole and graffiti detection model. My experience in software development aligns perfectly with your need for training these open-source models for better accuracy, especially with the day-night variation and diverse weather conditions. I believe in the power of data, and I'm adept at proper labeling/annotation for robust model training, a crucial aspect of this project. As an embedded systems developer proficient in using the NVIDIA Jetson hardware, I can effectively integrate the cameras on your vehicle to optimize data collection. With a solid grasp of Python and related tools like TensorFlow, Keras, OpenCV - among other relevant technologies - I can skillfully handle the dataset preparation, model training, and necessary customizations for different environments. My commitment to delivering high-quality solutions combined with my deep understanding of cybersecurity makes me a unique fit for this project. Security is a critical aspect when dealing with image data from cameras placed on vehicles. My ?????? ???????? approach ensures every angle is considered—from addressing vulnerabilities during data labeling/annotation yet preserving accuracy to incorporating robust security measures using your NVIDIA Jetson hardware for outside use. Let's build a system that not only detects but also protects.

@jesica46

Hello, After reviewing your project on domestic charter flight analysis, I clearly understand that this requires not just data processing, but strategic insight that supports financial and operational decision-making. As a Data Scientist with strong expertise in Python, R, and advanced Excel analytics, I specialize in transforming complex datasets and transcripts into structured, decision-ready insights. For your project, I will: ✔ Conduct structured qualitative and quantitative analysis aligned with your objectives ✔ Clean, validate, and structure raw datasets for analytical accuracy ✔ Apply statistical modeling and exploratory data analysis (EDA) using Python/R ✔ Identify key patterns, cost drivers, and performance indicators ✔ Deliver a clear analytical report with visualizations and actionable recommendations My focus is not just on analysis — but on delivering insights that directly support smarter, data-driven decisions. You can expect: • Well-documented methodology • Transparent working files (Python/R scripts or Excel models) • Clear visual dashboards (if required) • On-time delivery with professional communication I am ready to begin immediately and would welcome the opportunity to review your dataset to ensure the analysis fully aligns with your strategic goals. Looking forward to delivering measurable value to your project. Best regards,

@patrickag1214

Hello, I will enhance the performance and accuracy of your open-source models for pothole and graffiti detection, utilizing your additional datasets effectively. Given the complexities of outdoor environments, I anticipate challenges related to varying lighting and weather conditions, which I will address in the training process. With over five years of experience in machine learning and computer vision projects, I have successfully implemented similar solutions, including robust model training and data annotation for dynamic environments. My approach will involve detailed data labeling, followed by iterative training using techniques tailored for NVIDIA Jetson hardware to ensure optimized performance. To ensure we meet your expectations, I have a couple of questions: 1. What specific metrics or performance benchmarks are you aiming for? 2. Are there any particular considerations for the annotation process you’d like to address? I’m ready to start immediately and ensure your models are effectively trained and deployed for real-world scenarios. Let’s discuss how we can achieve your goals efficiently.

@Alesha1018

As an experienced and adaptable freelancer, I am well-versed in leveraging existing open source models and optimizing them for better performance - part of what makes me an excellent fit for your project. My skills in machine learning will be put to effective work as I train these models with the additional datasets you provide using meticulous labeling/annotation techniques. Furthermore, my experience deploying and fine-tuning models for diverse weather conditions and day-night operation makes me well-equipped for this task. Drawing from my background in civil, structural, and architectural design, I have a keen eye for detail which is critical during the annotation process. Moreover, my proficiency with AI & Machine Learning Integration will ensure that the resulting model is not only highly accurate but also tailored to your unique hardware configuration with Nvidia Jetson. To guarantee comprehensive solutions, I go beyond providing raw outputs and support them with robust documentation and technical drawings - a skill that would play invaluable role in your use case. Whether it's pothole or graffitiq detection or any other aspect of your project, I'm committed to delivering accurately, efficiently, creatively. Let’s collaborate to atualize your vision into practical and effective AI tool.

@simonp75

Hello, I would like to grab this opportunity and will work till you get 100% satisfied with my work. I'm a 10+ years of experienced full stack AI developer on Machine Learning (ML), Neural Networks, Image Processing, Open Source, Computer Vision, Deep Learning, Data Augmentation, Object Detection Please come over chat and discuss your requirement in a detailed way. Regards

@jeric5g

Hi there, I’ll extend open-source object detectors for potholes and graffiti with careful labeling (5-10k per class) and domain-specific augmentation to cover day/night and varied weather. Three cameras on an Nvidia Jetson edge device will run inference, while I tune (and re-train if needed) the models on your datasets to boost detection accuracy in real-world conditions. I approach it by aligning data, labeling with clear taxonomy, selecting lightweight backbones, and validating via hold-out and edge metrics. Best regards, Jeric

@MIndlabsAi6

Hello, I am Vishal Maharaj, with 20 years of experience in Computer Vision and Data Augmentation. I have carefully reviewed your project requirements and am confident in my ability to upgrade the pothole and graffiti detection models. To achieve this, I propose to first conduct thorough data labeling and annotation using the provided datasets. Next, I will further train the models using open source algorithms, optimizing them for performance in various conditions such as day-night scenarios and different weather conditions. Additionally, I will ensure compatibility with the hardware setup involving Nvidia Jetson and three cameras mounted on the vehicle. I am eager to discuss this project further with you. Please initiate a chat to explore how we can enhance the accuracy and efficiency of your models. Cheers, Vishal Maharaj

@andriip30

Hello, hope all is good. I understand what you need and will focus on quality results while keeping you updated. I have 10+ years of experience in Machine Learning (ML), Deep Learning. I have completed similar projects. Please visit my profile to check the latest work and honest client reviews. If this sounds good, connect in chat and we can start. Regards.

@rustomc

Hi there, I hear your goal: upgrade pothole and graffiti detection with open-source models, extended with new labeled data, optimized for day-night and varying weather, running on three Nvidia Jetson devices on a vehicle. I have spent the last 4 years solving exactly this type of edge ML and CV deployment, from data labeling to model fine-tuning and edge-optimized inference. Here’s the plan: 1) curate and annotate your 5-10k samples per case (pothole, graffiti) with consistent bounding boxes and attributes for lighting/weather. 2) apply targeted data augmentation (lighting shifts, weather, motion blur) to expand robustness. 3) train open-source detectors (e.g., YOLO/Detectron2) with transfer learning for pothole and graffiti classes, validate on hold-out sets, and quantify day/night performance. 4) optimize and quantize models for Nvidia Jetson, implement efficient pre/post-processing, and build a lightweight NVIDIA TensorRT pipeline. 5) deploy and test on the three cameras in real-time, with edge-first inference and remote monitoring. Best regards,