1 citations · 1 across the 5 of their papers we have counts for
5 papers
A Generative Adversarial Approach to Adversarial Attacks Guided by Contrastive Language-Image Pre-trained Model
Sampriti Soor, Alik Pramanick, Jothiprakash K +1
The rapid growth of deep learning has brought about powerful models that can handle various tasks, like identifying images and understanding language. However, adversarial attacks,…
Trans-defense: Transformer-based Denoiser for Adversarial Defense with Spatial-Frequency Domain Representation
Alik Pramanick, Mayank Bansal, Utkarsh Srivastava +2
In recent times, deep neural networks (DNNs) have been successfully adopted for various applications. Despite their notable achievements, it has become evident that DNNs are vulner…
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer
Alik Pramanick, Utsav Bheda, Arijit Sur
Recently, transformers have captured significant interest in the area of single-image super-resolution tasks, demonstrating substantial gains in performance. Current models heavily…
Harnessing Multi-resolution and Multi-scale Attention for Underwater Image Restoration
Alik Pramanick, Arijit Sur, V. Vijaya Saradhi
Underwater imagery is often compromised by factors such as color distortion and low contrast, posing challenges for high-level vision tasks. Recent underwater image restoration (UI…
Segmentation of tibiofemoral joint tissues from knee MRI using MtRA-Unet and incorporating shape information: Data from the Osteoarthritis Initiative
Akshay Daydar, Alik Pramanick, Arijit Sur +1
Knee Osteoarthritis (KOA) is the third most prevalent Musculoskeletal Disorder (MSD) after neck and back pain. To monitor such a severe MSD, a segmentation map of the femur, tibia…