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$60 USD / time

patna,

india

$60 USD / time

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Tilmeldt oktober 31, 2020

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Datakalp

@TheDatakalp

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$60 USD / time

patna,

india

$60 USD / time

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Harnessing the power of AI for a better tomorrow.

We’re a team of Data Scientists, Engineers, Machine Learning Experts, with collective 30+ years of different domain experience in Applied AI. The Team is led by Dr. Kalpit Desai, a renowned AI practitioner with 14+ years of experience post Ph.D. Our areas of technical expertise are Sensor Intelligence, Computer Vision, Text Mining, Stats and Optimization, and many more. Services we offer: 1.Contract R & D. 2.Consultacy. 3.Model Audit. 4.Workshop. Industries we serve: [login to view URL]. 2.Defence and Security. 3.Reail. 4.Manufacturing. [login to view URL]. 6.Hospitality. and many more. For more details please do visit [login to view URL]

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Portfolio-mappe

8495399

It associates images of the same person taken from different cameras or from the same camera on different occasions.
Object Re-ID is currently concentrated in the field of person Re-ID and vehicle Re-ID, which is mainly used to realize the cross-vision tracking of person/vehicle and trajectory prediction.

Datakalp Re-identification.

HygieneAI - a platform to help businesses, hospitals, educational institutes, and government offices return to normalcy safely post unlock.
This technology makes it possible to easily determine whether someone is following each of the 9 steps for handwashing recommended by WHO, reducing the number of man-hours required for intrusive visual checks by inspectors for on-site sanitation management. Moving forward, Datakalp envisions this technology being used in a variety of other contexts, including in medical facilities, schools, hotels, and venues for large events, and plans to conduct field trials and additional research and development into it as a potential solution for its AI portfolio in the future.
HygineAI Demo Video : http://datakalp.com/safehands

Hygine AI

Detect if people are wearing a face mask
Detect if people are keeping a safe social distance (using CCTV)
Detect if people are washing their hands properly

SafeAir

Detect and identify people, vehicles, animals, weapons
Detect perimeter breach
Detect unusual activity (e.g. fighting, crawling, explosion etc)
Real-time alerts

Vajra

It detects and raises real-time ticket if Aircraft deviates from its trajectory.
Learn ‘normal’ routes from past flights data
Determine if the observed deviation in a transport aircraft could be due to weather
Determine if a given fighter jet is an imposter (IFF) based on its trajectory
Real-time alerts

Maargan

8495399

Datakalp Re-identification.

Hygine AI

SafeAir

Vajra

Maargan

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Erfaring

Datakalp

okt. 2018 - Nuværende

I am a Ph.D. in Biomedical Engineering from the University of North Carolina at Chapel Hill, North Carolina. I have 15+ years of corporate experience in Data Science, Artificial Intelligence, Computer Vision, NLP, Sensor Intelligence, and many more and I was associated with companies like GE, Clustr Data/Tally Analytics, Bidgely, etc. Some of our clients include Defense (India), Airport Authority, Retail Bank, Retail Apparel chain, Farm-to-Fork business etc.

Uddannelse

Ph.D.

North Carolina State University,

United States

2002 - 2006

(4 år)

Kvalifikationer

IEEE International Data Mining Contest

2011

The contest on Wikipedia data hosted by kaggle.

GE Global Research - John F Welch Technology Center

2012

For technical contribution toward Wind Farm analytics projects.

Publikationer

Double Ramp Loss Based Reject Option Classifier.

Springer, Cham

Our approach is based on minimizing regularized risk under the double ramp loss using the difference of convex programming. We show the effectiveness of our approach through experiments on synthetic and benchmark datasets. Our approach performs better than the state of the art reject option classification approaches.

Insights from the Wikipedia Contest.

IEEE

The objective for the participants was to develop models to predict the number of edits that an editor will make in the future five months based on the editing history of the editor. Here we describe the approach we followed for developing predictive models towards this goal, the results that we obtained, and the modeling insights that we gained from this exercise.

Hemodynamic-impact-based prioritization of ventricular tachycardia alarms

IEEE

The focus of this study is to provide guidance on determining whether a technically-correct V-tach alarm is clinically-actionable by determining its “hemodynamic impact”. A supervisory learning approach based on conditional inference trees to determine the hemodynamic impact of a V-tach alarm based on extracted features is described.