11 citations · 19 across the 7 of their papers we have counts for
7 papers
SOUL: A Semi-supervised Open-world continUal Learning method for Network Intrusion Detection
Suresh Kumar Amalapuram, Shreya Kumar, Bheemarjuna Reddy Tamma +1
Fully supervised continual learning methods have shown improved attack traffic detection in a closed-world learning setting. However, obtaining fully annotated data is an arduous t…
Subjective and Objective Quality Assessment Methods of Stereoscopic Videos with Visibility Affecting Distortions
Sria Biswas, Balasubramanyam Appina, Priyanka Kokil +1
We present two major contributions in this work: 1) we create a full HD resolution stereoscopic (S3D) video dataset comprised of 12 reference and 360 distorted videos. The test sti…
Enhanced Astronomical Source Classification with Integration of Attention Mechanisms and Vision Transformers
Srinadh Reddy Bhavanam, Sumohana S. Channappayya, P. K. Srijith +1
Accurate classification of celestial objects is essential for advancing our understanding of the universe. MargNet is a recently developed deep learning-based classifier applied to…
Inpainting the Gaps: A Novel Framework for Evaluating Explanation Methods in Vision Transformers
Lokesh Badisa, Sumohana S. Channappayya
The perturbation test remains the go-to evaluation approach for explanation methods in computer vision. This evaluation method has a major drawback of test-time distribution shift…
Minimizing Energy Costs in Deep Learning Model Training: The Gaussian Sampling Approach
Challapalli Phanindra Revanth, Sumohana S. Channappayya, C Krishna Mohan
Computing the loss gradient via backpropagation consumes considerable energy during deep learning (DL) model training. In this paper, we propose a novel approach to efficiently com…
Discrete Control in Real-World Driving Environments using Deep Reinforcement Learning
Avinash Amballa, Advaith P., Pradip Sasmal +1
Training self-driving cars is often challenging since they require a vast amount of labeled data in multiple real-world contexts, which is computationally and memory intensive. Res…