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Quantum Vision Transformers [PDF]
QuantumIn this work, quantum transformers are designed and analysed in detail by extending the state-of-the-art classical transformer neural network architectures known to be very performant in natural language processing and image analysis.
El Amine Cherrat +5 more
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Transformers in Vision: A Survey [PDF]
ACM Computing Surveys, 2022 Astounding results from Transformer models on natural language tasks have intrigued the vision community to study their application to computer vision problems. Among their salient benefits, Transformers enable modeling long dependencies between input sequence elements and support parallel processing of sequence as compared to recurrent networks, e.g.,
Salman Khan +2 more
exaly +3 more sources
ViTFER: Facial Emotion Recognition with Vision Transformers
Applied System Innovation, 2022 In several fields nowadays, automated emotion recognition has been shown to be a highly powerful tool. Mapping different facial expressions to their respective emotional states is the main objective of facial emotion recognition (FER).
Aayushi Chaudhari +3 more
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Self-attention in vision transformers performs perceptual grouping, not attention
Frontiers in Computer Science, 2023 Recently, a considerable number of studies in computer vision involve deep neural architectures called vision transformers. Visual processing in these models incorporates computational models that are claimed to implement attention mechanisms. Despite an
Paria Mehrani, John K. Tsotsos
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Denoising Vision Transformers [PDF]
Accepted to ECCV2024. Project website: https://jiawei-yang.github.io/DenoisingViT/
Jiawei Yang +8 more
openalex +3 more sources
Art authentication with vision transformers
Neural Computing and Applications, 2023 AbstractIn recent years, transformers, initially developed for language, have been successfully applied to visual tasks. Vision transformers have been shown to push the state of the art in a wide range of tasks, including image classification, object detection, and semantic segmentation.
Eric Postma
exaly +4 more sources
Vision Transformers for Remote Sensing Image Classification
Remote Sensing, 2021 In this paper, we propose a remote-sensing scene-classification method based on vision transformers. These types of networks, which are now recognized as state-of-the-art models in natural language processing, do not rely on convolution layers as in ...
Yakoub Bazi +4 more
doaj +3 more sources
Vision Transformers in medical computer vision—A contemplative retrospection
Engineering Applications of Artificial Intelligence, 2023 Recent escalation in the field of computer vision underpins a huddle of algorithms with the magnificent potential to unravel the information contained within images. These computer vision algorithms are being practised in medical image analysis and are transfiguring the perception and interpretation of Imaging data.
Muhammad Moazam Fraz
exaly +3 more sources
Deep learning for mango leaf disease identification: A vision transformer perspective
HeliyonOver the last decade, the use of machine learning in smart agriculture has surged in popularity. Deep learning, particularly Convolutional Neural Networks (CNNs), has been useful in identifying diseases in plants at an early stage.
Md. Arban Hossain +3 more
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Rosette Trajectory MRI Reconstruction with Vision Transformers [PDF]
TomographyIntroduction: An efficient pipeline for rosette trajectory magnetic resonance imaging reconstruction is proposed, combining the inverse Fourier transform with a vision transformer (ViT) network enhanced with a convolutional layer.
Muhammed Fikret Yalcinbas +4 more
doaj +2 more sources