18 citations · 57 across the 18 of their papers we have counts for
20 papers
FedSSMCoOp: SSM Encoders for light-weight Federated Prompt Learning for Few-shot Classification
Ankita Das, Ambarish Parthasarathy, Sumohana S. Channappayya +1
Vision-Language Models (VLMs) have shown strong performance across a wide range of downstream vision tasks, thanks to the complementary information contained in the respective doma…
SEED: Semi-supervised Continual MalwarE Detection for Tackling ConcEpt Drift on a BuDget
Suresh Kumar Amalapuram, Bikraj Shresta, Siva Ram murthy Chebiyam +2
Machine learning based malware detectors become obsolete over time due to concept drift in benign and malware applications. Recent methods rely on fully labeled data and use hierar…
Exploring Compositionality in Vision Transformers using Wavelet Representations
Akshad Shyam Purushottamdas, Pranav K Nayak, Divya Mehul Rajparia +4
While insights into the workings of the transformer model have largely emerged by analysing their behaviour on language tasks, this work investigates the representations learnt by…
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…
Cosmic Ray Rejection with Attention Augmented Deep Learning
S. R. Bhavanam, Sumohana S. Channappayya, P. K. Srijith +1
Cosmic Ray (CR) hits are the major contaminants in astronomical imaging and spectroscopic observations involving solid-state detectors. Correctly identifying and masking them is a…
Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark
Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis +22
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor. Human-centered segmentation, which i…
Can Perceptual Guidance Lead to Semantically Explainable Adversarial Perturbations?
P Charantej Reddy, Aditya Siripuram, Sumohana S. Channappayya
It is well known that carefully crafted imperceptible perturbations can cause state-of-the-art deep learning classification models to misclassify. Understanding and analyzing these…
Deep No-reference Tone Mapped Image Quality Assessment
Chandra Sekhar Ravuri, Rajesh Sureddi, Sathya Veera Reddy Dendi +2
The process of rendering high dynamic range (HDR) images to be viewed on conventional displays is called tone mapping. However, tone mapping introduces distortions in the final ima…
Quality Aware Generative Adversarial Networks
Parimala Kancharla, Sumohana S. Channappayya
Generative Adversarial Networks (GANs) have become a very popular tool for implicitly learning high-dimensional probability distributions. Several improvements have been made to th…
Streaming Video QoE Modeling and Prediction: A Long Short-Term Memory Approach
Nagabhushan Eswara, S Ashique, Anand Panchbhai +5
HTTP based adaptive video streaming has become a popular choice of streaming due to the reliable transmission and the flexibility offered to adapt to varying network conditions. Ho…
Novel Light Weight Compressed Data Aggregation Using Sparse Measurements for IoT Networks
Amarlingam M, Pradeep Kumar Mishra, P Rajalakshmi +2
Optimal data aggregation aimed at maximizing IoT network lifetime by minimizing constrained on-board resource utilization continues to be a challenging task. The existing data aggr…
Modeling Continuous Video QoE Evolution: A State Space Approach
Nagabhushan Eswara, Hemanth P. Sethuram, Soumen Chakraborty +3
A rapid increase in the video traffic together with an increasing demand for higher quality videos has put a significant load on content delivery networks in the recent years. Due…
Estimating Depth-Salient Edges And its Application To Stereoscopic Image Quality Assessment
Sameeulla Khan Md, Sumohana Channappayya
The human visual system pays attention to salient regions while perceiving an image. When viewing a stereoscopic 3D (S3D) image, we hypothesize that while most of the contribution…
No Reference Stereoscopic Video Quality Assessment Using Joint Motion and Depth Statistics
Appina Balasubramanyam, Jalli Akshith, Battula Shanmukh Srinivas +1
We present a no reference (NR) quality assessment algorithm for assessing the perceptual quality of natural stereoscopic 3D (S3D) videos. This work is inspired by our finding that…
Optical Character Recognition (OCR) for Telugu: Database, Algorithm and Application
Chandra Prakash Konkimalla, Manikanta Srikar Yellapragada, Trishal Gayam +2
Telugu is a Dravidian language spoken by more than 80 million people worldwide. The optical character recognition (OCR) of the Telugu script has wide ranging applications including…
Subjective Assessment of H.264 Compressed Stereoscopic Video
Manasa K, Balasubramanyam Appina, Sumohana S. Channappayya
The tremendous growth in 3D (stereo) imaging and display technologies has led to stereoscopic content (video and image) becoming increasingly popular. However, both the subjective…