Dr. Chevella Anil Kumar
VNR Vignana Jyothi Institute of Engineering and Technology
About
Dr. Chevella Anil Kumar is an Assistant Professor in the Department of ECE at VNR Vignana Jyothi Institute of Engineering and Technology in Hyderabad, Telangana, India. Received B.Tech and M.Tech degree in Electronics and Communication Engineering from JNTU Hyderabad with a Distinction. He was awarded a Doctor of Philosophy (Ph.D.) from Jawaharlal Nehru Technological University Hyderabad. He currently serves as the Faculty Advisor for the IEEE Hyderabad SPS Student Branch at VNRVJIET. He has total 9 years of experience in Research and Teaching, He published Several Research papers in national/international journals, conferences and book chapters indexed by SCI, Scopus and Web of Science and also, he published/Granted four patents. He was given the expert talks in various National and International workshops Sponsored by AICTE and IEEE Hyderabad Section.
Dr. Anil Kumar has worked as a Junior Research Fellow for various R&D research projects funded by UGC, ISRO, and AICTE-RPS. Especially he developed a TTS voice module for ISRO for GAGANYAN Project. His research focuses on image, speech, and video signal processing, using machine learning and deep learning.
Employment
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VNR Vignana Jyothi Institute of Engineering and Technology Assistant Professor2022 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (32)
- Vehicle Detection and Counting using YOLOv11 on Raspberry Pi 5 Save
- Affective Speech-to-Speech Chatbot for Context-Aware Human-Machine Interaction Save
- Semantic Feature-Based Image Retrieval Using Vgg19 Model: Corel Images Dataset and Elu Activation Function Save
- A deep learning-based system for automated image caption synthesis Save
- AI on Patrol: An Intelligent System for Helmet Detection and Traffic Enforcement Save
- AI-Driven Smart Healthcare System for Monitoring Drought and Analyzing Climate Change Impacts in Healthcare for Medical 4.0 Save
- An Intelligent System to Identify the Emotions in the Text Using a Hybrid Deep Learning Model Save
- Analysis of human emotions through speech using deep learning fusion technique for Industry 5.0 Save
- Crack Detection and Structural Assessment in Bridges Using Generative Adversarial Networks Save
- Design and Verification of APB Protocol Save