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pro vyhledávání: '"Singh, Satish"'
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