Results 11 to 20 of about 9,677,595 (330)
Understanding Robustness of Transformers for Image Classification [PDF]
IEEE International Conference on Computer Vision, 2021 Deep Convolutional Neural Networks (CNNs) have long been the architecture of choice for computer vision tasks. Recently, Transformer-based architectures like Vision Transformer (ViT) have matched or even surpassed ResNets for image classification ...
Srinadh Bhojanapalli +5 more
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Applied Sciences, 2023 Transformers are models that implement a mechanism of self-attention, individually weighting the importance of each part of the input data. Their use in image classification tasks is still somewhat limited since researchers have so far chosen ...
J. Maurício +2 more
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Multimodal Fusion Transformer for Remote Sensing Image Classification [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Vision transformers (ViTs) have been trending in image classification tasks due to their promising performance when compared with convolutional neural networks (CNNs).
S. K. Roy +5 more
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Multi-column deep neural networks for image classification [PDF]
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012 Traditional methods of computer vision and machine learning cannot match human performance on tasks such as the recognition of handwritten digits or traffic signs.
D. Ciresan, U. Meier, J. Schmidhuber
semanticscholar +1 more source
Graph Convolutional Networks for Hyperspectral Image Classification [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2020 Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classification due to their ability to capture spatial–spectral feature representations.
D. Hong +5 more
semanticscholar +1 more source
Label-Embedding for Image Classification [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016 IEEE TPAMI ...
Akata, Zeynep +3 more
openaire +5 more sources
npj Digit. Medicine, 2023 Advancements in deep learning and computer vision provide promising solutions for medical image analysis, potentially improving healthcare and patient outcomes.
Shih-Cheng Huang +5 more
semanticscholar +1 more source
Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning [PDF]
Computer Vision and Pattern Recognition, 2020 We address the challenging problem of whole slide image (WSI) classification. WSIs have very high resolutions and usually lack localized annotations.
Bin Li, Yin Li, K. Eliceiri
semanticscholar +1 more source
Single-Source Domain Expansion Network for Cross-Scene Hyperspectral Image Classification [PDF]
IEEE Transactions on Image Processing, 2022 Currently, cross-scene hyperspectral image (HSI) classification has drawn increasing attention. It is necessary to train a model only on source domain (SD) and directly transferring the model to target domain (TD), when TD needs to be processed in real ...
Yuxiang Zhang +4 more
semanticscholar +1 more source
A COLORING ALGORITHM FOR IMAGE CLASSIFICATION [PDF]
Applied Computational Intelligence, 2004 In this paper we present a pixel coloring algorithm, to be considered as a tool in fuzzy classification. Such an algorithm is based upon a sequential application of a divisive binary procedure on a fuzzy graph associated to the image to be classified, taking into account surrounding pixels.
Gómez González, Daniel +3 more
openaire +3 more sources