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Swin Transformer for Robust CGI Images Detection: Intra- and Inter-Dataset Analysis across Multiple Color Spaces
Preeti Mehta, Aman Sagar, Suchi Kumari
This study aims to address the growing challenge of distinguishing computer-generated imagery (CGI) from authentic digital images across three different color spaces; RGB, YCbCr, a…
Integrating Deep Feature Extraction and Hybrid ResNet-DenseNet Model for Multi-Class Abnormality Detection in Endoscopic Images
Aman Sagar, Preeti Mehta, Monika Shrivastva +1
This paper presents a deep learning framework for the multi-class classification of gastrointestinal abnormalities in Video Capsule Endoscopy (VCE) frames. The aim is to automate t…
Enhancing Image Authenticity Detection: Swin Transformers and Color Frame Analysis for CGI vs. Real Images
Preeti Mehta, Aman Sagar, Suchi Kumari
The rapid advancements in computer graphics have greatly enhanced the quality of computer-generated images (CGI), making them increasingly indistinguishable from authentic images c…
Swin Transformer for Robust Differentiation of Real and Synthetic Images: Intra- and Inter-Dataset Analysis
Preetu Mehta, Aman Sagar, Suchi Kumari
\textbf{Purpose} This study aims to address the growing challenge of distinguishing computer-generated imagery (CGI) from authentic digital images in the RGB color space. Given the…
Enhancing Eye Disease Diagnosis with Deep Learning and Synthetic Data Augmentation
Saideep Kilaru, Kothamasu Jayachandra, Tanishka Yagneshwar +1
In recent years, the focus is on improving the diagnosis of diabetic retinopathy (DR) using machine learning and deep learning technologies. Researchers have explored various appro…
Domain Generalized Recaptured Screen Image Identification Using SWIN Transformer
Preeti Mehta, Aman Sagar, Suchi Kumari
An increasing number of classification approaches have been developed to address the issue of image rebroadcast and recapturing, a standard attack strategy in insurance frauds, fac…