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Research Organization of Science and Technology

 (Male)
 BHARATH   RAMKRISHNA  Assistant Professor

■Graduate school/University/other
05/2008  Jawaharlal Nehru Technological University Hyderabad  Kuppam Engineering College  Electronics and Communication Systems  Completed
10/2012  Jawaharlal Nehru Technological University Anantapur  Madanapalli Institute of Technology and Science  Digital Electronics and Communication Systems  Master's course  Completed
08/2018  Indian Institute of Technology Hyderabad  Indian Institute of Technology Hyderabad  Electrical Engineering  Doctoral course  Completed
■Career history
02/05/2018-02/04/2019  Project Officer
■Subject of research
Developing the AI and model-based algorithms for autonomous vehicles in unconstructed roads
■Research summary
Development of AI-based Recognition Environment for Autonomous Driving of Cars in Unconstructured Roads

 The current autonomous driving vehicles will work only in the constrained environments like structured roads consisting of lane markings and in nice environment conditions, etc. The technology for the autonomous driving in situations like unconstructed roads, adverse wind conditions, hail, etc., have not been fully developed. There is a high necessity to develop the technology for unstructured and different daylight conditions since one need to encounter these conditions very often.

Recognizing and understanding the driving environment via sensors in real-time is a key technological aspect in autonomous driving. My research is mainly focused on developing the recognition environment for unstructured roads based on camera and Lidar sensors. I will be particularly looking in deep learning algorithms for object detection and detecting the safe region for autonomous driving.
■Research keywords
Machine Learning, Computer Vision, Image Processing, Medical Image Analysis 
■Research activities   (Even top three results are displayed. In View details, all results for public presentation are displayed.)

Papers
Automated Quantification of Ultrasonic Fatty Liver Texture based on Curvelet Transform and SVD  R. Bharath Pradeep Kumar Mishra, P Rajalakshmi  Elsevier Biocybernetics and Biomedical Engineering  38/ 1, 189-197  2018
Multi-modal Framework for Automatic Detection of Diagnostically Important Regions in Nonalcoholic Fatty Liver Ultrasonic Images  R. Bharath, P Rajalakshmi, Abdul Mateen Mohammad  Elsevier Biocybernetics and Biomedical Engineering  38/ 3, 586-601  2018
Computer Aided Abnormality Detection for Kidney on FPGA based IoT Enabled Portable Ultrasound Imaging System  K. Divya Krishna, Vivek Akkala, R. Bharath, P. Rajalakshmi, Mohammed Abdul Mateen, S. N. Merchant, and U. B. Desai  Elsevier Innovation in Research and Biomedical Engineering  37/ 4, 189-197  05/2016
View details...

Research presentations
WebRTC based invariant scattering convolution network
for automated validation of ultrasonic videos for IoT enabled tele-sonography  IEEE World Forum IoT  2018
A Novel Computer-Aided Diagnosis Framework Using Deep Learning for Classification of Fatty Liver Disease in Ultrasound Images  IEEE Healthcom  2018
Classification of Nonalcoholic Fatty Liver Texture Using Convolution Neural Networks  IEEE Healthcom  2018
View details...
■Message from researcher
Development of AI based recognition and understanding algorithms of roads for autonomous driving
 I am interested in the development of detection and understanding of roads for safe driving of autonomous vehicles. I am mainly focused in the development of deep learning algorithms for object detection and also to detect the safe patterns on the road for autonomous navigation. Lidar and camera sensors will be employed to detect the objects and for detection of the safe driving paths.
■URL
 Intelligent Vehicle System Laboratory
■Tel
0775612774
■Research keywords(on a multiple-choice system)
Intelligent robotics
Learning support system