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$25 USD / hour
Flag of INDIA
india, india
$25 USD / hour
It's currently 4:53 PM here
Joined March 6, 2014
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Angad Y.

@yennamangad

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$25 USD / hour
Flag of INDIA
india, india
$25 USD / hour
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Computer Vision Research Engineer

2.5+ years of experience in data science and deep learning with strong computer vision and algorithmic problem-solving ability. ‎Wide range of experience in data science/ machine learning/ deep learning space from simple machine learning algorithms to complex deep learning neural networks
Freelancer Python Developers India
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Portfolio

6666495
Development of Human Gait Kinematic Analysis System using Microsoft Kinect The virtual measurement system provides several advantages over the conventional one like a noncontact sensor, ruggedness, etc. The system is developed for the detection of gait characteristics from the Kinect image sensor. There is a centralized influence by hip and knee on human gait and it requires a continuous monitoring tool for effective rehabilitation. Kinect gives the 30 fps 3D motion capturing capability of the human skeleton. It also calculates joint skeleton information along with relative angles when the subject walks in a Kinect field of view. The result were compared with the standard electro goniometer system. The system is validated for knee joint angles at different gait conditions and also by changing the position of the Kinect image sensor right and left. The study showed that the joint angles between both systems give the variation of the RMSE value from ~4.27° to ~4.91° for the right knee.
Development of Human Gait Kinematic Analysis System
6666485
Pose estimation refers to computer vision techniques that detect human figures in images and videos. Pose an estimation has many uses, from interactive installations that react to the body to augmented reality, animation, fitness uses, and more.
Development of real-time system for Human Body Pose
6666479
Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background, expression, hairstyle, and glasses. here using deep learning models to solve these problems.
Design a real-time system for Face Identification
6666447
Integrating Robotic Gait Training System
6666495
Development of Human Gait Kinematic Analysis System using Microsoft Kinect The virtual measurement system provides several advantages over the conventional one like a noncontact sensor, ruggedness, etc. The system is developed for the detection of gait characteristics from the Kinect image sensor. There is a centralized influence by hip and knee on human gait and it requires a continuous monitoring tool for effective rehabilitation. Kinect gives the 30 fps 3D motion capturing capability of the human skeleton. It also calculates joint skeleton information along with relative angles when the subject walks in a Kinect field of view. The result were compared with the standard electro goniometer system. The system is validated for knee joint angles at different gait conditions and also by changing the position of the Kinect image sensor right and left. The study showed that the joint angles between both systems give the variation of the RMSE value from ~4.27° to ~4.91° for the right knee.
Development of Human Gait Kinematic Analysis System
6666485
Pose estimation refers to computer vision techniques that detect human figures in images and videos. Pose an estimation has many uses, from interactive installations that react to the body to augmented reality, animation, fitness uses, and more.
Development of real-time system for Human Body Pose
6666479
Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background, expression, hairstyle, and glasses. here using deep learning models to solve these problems.
Design a real-time system for Face Identification
6666447
Integrating Robotic Gait Training System

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Experience

Researcher PhD

IIIT hyderabad
Jan 2020 - Present
Center for Visual Information Technology (CVIT)

Computer Vision Research Engineer

deepedge.ai
Apr 2018 - Present
R&D deep learning & computer vision

Junior Research Fellow

Indian Institute of Technology Gandhinagar India.
Dec 2017 - Mar 2018 (3 months, 1 day)
Integrating Robotic Gait Training System with Virtual Reality for Gait Rehabilitation - a novel approach in Neurorehabilitation, IIT Gandhinagar. Brief :​ During gait training in persons with central nervous system (CNS) movement disorders, virtual reality (VR) can offer added value by providing task-specific gait training in more interactive and motivating environments.

Education

PhD Center for Visual Information Technology (CVIT) IIIT, Gachibowli, Gachibowli, Hyderabad

International Institute of Information Technology, India 2020
(Less than a year)

Master of Technology, Instrumentation Engineering, GOVT .College S.G.G.S I.E & T, Nanded

Swami Ramanand Teerth Marathwada University, India 2013 - 2015
(2 years)

Qualifications

TensorFlow and the Google Cloud ML Engine for Deep Learning

Udacity
2019
TensorFlow and the Google Cloud ML Engine for Deep Learning

Computer Vision Nanodegree

Udacity
2019
Computer Vision Nanodegree

Deep Learning

GUVI Geek Networks, IITM Research Park
2019
Deep Learning

Publications

Implementation of Affordable Joint Angle Measurement for Gait Analysis using Kinect Sensor

IOSR Journal of Electronics and Communication Engineering
‘Yennam Angad, Sumeet Shandilya, Neelesh Kumar,”​ Implementation of Affordable Joint Angle Measurement for Gait Analysis using Kinect Sensor​ ,” IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) e-ISSN: 2278-2834,p- ISSN:2278-8735.PP 57-60.

​ Development of kinematic measurement system with Kinect sensor

IEEE
A. Yennam, K. Sherwani and N. Kumar, "​ Development of kinematic measurement system with Kinect sensor​ ," 2015 Annual IEEE India Conference (INDICON), New Delhi, 2015, pp. 1-5

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Top Skills

Python
Electronics
Matlab and Mathematica
Electrical Engineering
Machine Learning (ML)

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