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pro vyhledávání: '"Dubey, Shiv"'
Convolutional Neural Networks (CNNs) have made remarkable strides; however, they remain susceptible to vulnerabilities, particularly in the face of minor image perturbations that humans can easily recognize. This weakness, often termed as 'attacks',
Externí odkaz:
http://arxiv.org/abs/2409.03458
In recent years, Vision Transformers (ViTs) have shown promising classification performance over Convolutional Neural Networks (CNNs) due to their self-attention mechanism. Many researchers have incorporated ViTs for Hyperspectral Image (HSI) classif
Externí odkaz:
http://arxiv.org/abs/2404.13252
Facial super-resolution/hallucination is an important area of research that seeks to enhance low-resolution facial images for a variety of applications. While Generative Adversarial Networks (GANs) have shown promise in this area, their ability to ad
Externí odkaz:
http://arxiv.org/abs/2401.15366
Unsupervised image retrieval aims to learn the important visual characteristics without any given level to retrieve the similar images for a given query image. The Convolutional Neural Network (CNN)-based approaches have been extensively exploited wi
Externí odkaz:
http://arxiv.org/abs/2401.15362
Image super-resolution aims to synthesize high-resolution image from a low-resolution image. It is an active area to overcome the resolution limitations in several applications like low-resolution object-recognition, medical image enhancement, etc. T
Externí odkaz:
http://arxiv.org/abs/2312.01999
Image super-resolution generation aims to generate a high-resolution image from its low-resolution image. However, more complex neural networks bring high computational costs and memory storage. It is still an active area for offering the promise of
Externí odkaz:
http://arxiv.org/abs/2310.13216
Autor:
Dubey, Shiv Ram, Singh, Satish Kumar
Generative Adversarial Networks (GANs) have been very successful for synthesizing the images in a given dataset. The artificially generated images by GANs are very realistic. The GANs have shown potential usability in several computer vision applicat
Externí odkaz:
http://arxiv.org/abs/2302.08641
Autor:
Kumarapu, Laxman, Dubey, Shiv Ram, Mukherjee, Snehasis, Mohan, Parkhi, Vinnakoti, Sree Pragna, Karthikeya, Subhash
With the rise of handy smart phones in the recent years, the trend of capturing selfie images is observed. Hence efficient approaches are required to be developed for recognising faces in selfie images. Due to the short distance between the camera an
Externí odkaz:
http://arxiv.org/abs/2302.07245
In this paper, we present electromyography analysis of human activity - database 1 (EMAHA-DB1), a novel dataset of multi-channel surface electromyography (sEMG) signals to evaluate the activities of daily living (ADL). The dataset is acquired from 25
Externí odkaz:
http://arxiv.org/abs/2301.03325