Vineeth Vijayaraghavan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
12
Venues
6
Active years
2018–2021
Best venue rank
A*
Where they publish
Papers
12 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2021 | AusDM | SOMPS-Net: Attention Based Social Graph Framework for Early Detection of Fake Health News. | Prasannakumaran Dhanasekaran, Harish Srinivasan, S. Sowmiya Sree, Sri Gayathri Devi I, Saikrishnan Sankar, Vineeth Vijayaraghavan |
| 2021 | ICCS | A Non-intrusive Machine Learning Solution for Malware Detection and Data Theft Classification in Smartphones. | Sai Vishwanath Venkatesh, D. Prasannakumaran, Joish J. Bosco, Pravin Kumaar R, Vineeth Vijayaraghavan |
| 2021 | ICMLA | End-to-End Optimized Arrhythmia Detection Pipeline using Machine Learning for Ultra-Edge Devices. | Sideshwar J. B, Sachin Krishan T, Vishal Nagarajan, Shanthakumar S, Vineeth Vijayaraghavan |
| 2021 | ICMLA | BP-Net: Efficient Deep Learning for Continuous Arterial Blood Pressure Estimation using Photoplethysmogram. | Rishi Vardhan K, Vedanth S, Poojah G, Abhishek K, Nitish Kumar M, Vineeth Vijayaraghavan |
| 2021 | ICMLA | Critical State Detection for Adversarial Attacks in Deep Reinforcement Learning. | Praveen Kumar R, I Niranjan Kumar, Sujith Sivasankaran, A. Mohan Vamsi, Vineeth Vijayaraghavan |
| 2020 | ICMLA | Adversarial Patch Defense for Optical Flow Networks in Video Action Recognition. | Adithya Prem Anand, Gokul H, Harish Srinivasan, Pranav Vijay, Vineeth Vijayaraghavan |
| 2020 | ICMLA | Defending Against Localized Adversarial Attacks on Edge-Deployed Monocular Depth Estimators. | Nanda H. Krishna, Praveen Kumar R, Rishi Vardhan K, Vineeth Vijayaraghavan |
| 2020 | ICMLA | End-to-End Deep Learning for Reliable Cardiac Activity Monitoring using Seismocardiograms. | Prithvi Suresh, Naveen Narayanan, Chakilam Vijay Pranav, Vineeth Vijayaraghavan |
| 2019 | ICDM | A Dynamically Adaptive Movie Occupancy Forecasting System with Feature Optimization. | Sundararaman Venkataramani, Ateendra Ramesh, Sharan Sundar S, Aashish Kumar Jain, Gautham Krishna Gudur, Vineeth Vijayaraghavan |
| 2019 | ICMLA | Scalable Deep Learning for Stress and Affect Detection on Resource-Constrained Devices. | Abhijith Ragav, Nanda Harishankar Krishna, Naveen Narayanan, Kevin Thelly, Vineeth Vijayaraghavan |
| 2019 | IWANN | DeepTrace: A Generic Framework for Time Series Forecasting. | Nithish B. Moudhgalya, Siddharth Divi, V. Adithya Ganesan, S. Sharan Sundar, Vineeth Vijayaraghavan |
| 2018 | Mobisys | HARNet: Towards On-Device Incremental Learning using Deep Ensembles on Constrained Devices. | Prahalathan Sundaramoorthy, Gautham Krishna Gudur, Manav Rajiv Moorthy, R. Nidhi Bhandari, Vineeth Vijayaraghavan |