June 11, 2024, 4:48 a.m. | Leonardo Scabini, Andre Sacilotti, Kallil M. Zielinski, Lucas C. Ribas, Bernard De Baets, Odemir M. Bruno

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.06136v1 Announce Type: cross
Abstract: Texture, a significant visual attribute in images, has been extensively investigated across various image recognition applications. Convolutional Neural Networks (CNNs), which have been successful in many computer vision tasks, are currently among the best texture analysis approaches. On the other hand, Vision Transformers (ViTs) have been surpassing the performance of CNNs on tasks such as object recognition, causing a paradigm shift in the field. However, ViTs have so far not been scrutinized for texture recognition, …

abstract analysis applications arxiv cnns computer computer vision convolutional convolutional neural networks cs.cv cs.lg extraction feature feature extraction image image recognition images networks neural networks recognition survey tasks texture transformers type vision vision transformers visual

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