Anil Garg
M M Deemed to be University, National Institute of Technology Kurukshetra
0000-0003-3884-6813
About
having teaching experience of more than 20 yrs. & completed Ph.D from NIT Kurukshetra. More than 90 papers have been published in various reputed National/International Journals/Conferences. My Google Scholar citation is 315, H-index-9, i10-index 9 & Scopus Citation is 88, H-index-4, i10-index 2. I have Guided 17 M.Tech Dissertations. I have also published one patent titled “Virtual Debate Chamber With Speech Enhancement” and is in process for the grant of the patent. I have performed the responsibilities as Guest Editor of “ International Journal of Speech technology” Published by Springer, ISSN- 1381-2416. I have also been selected as TPC Member, Program Committee and quality reviewer in the “International Conference on Recent Trends in Communication & Intelligent Systems” held on 20/11/2020- 21/11/2020 at Arya College of Engineering & I.T., Jaipur, Rajasthan, India. (Springer). I Have also perfomed various responsibilities -USIC Co-ordinator, RAC coordinator, BOS member, FET member, Member PGC, Reviewer of various National/International SCI/Scopus indexed journals etc.
Employment
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M M Deemed to be University Associate Professor2002 - Present
Education
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National Institute of Technology Kurukshetra Ph. D2011 - 2020
Projects & Funding
Projects & funding information is unavailable.
Publications (33)
- SrTaO-DRNN: Search and track optimization-enabled distributed recurrent neural network for sarcasm detection Save
- An Overview of Machine Learning and Deep Learning Approaches to Brain Tumor Detection and Classification Save
- Recognising Hand Gestures in 3-D using a Stereo Camera Save
- “Structures and Sensors of Polymer Optical Fibres For last Mile Networks Save
- Agriculture Field Data Monitoring & Recording Through Smart Irrigtion Model Save
- “Unveiling the Power of Neuromorphic Computing:An Introductory Overview Save
- Precise Water Saving Model Through NB & KNN Save
- Speech Enhancement using Long Short Memory with Trained Speech Features and Adaptive Wiener filtering Save
- Deep Convolution Neural Network based Speech Enhancement using Extensive Speech Features Save
- A hybrid approach for speech enhancement using Bionic wavelet transform and Butterworth filter Save