Results 41 to 50 of about 82,164 (262)
The Multiscale Surface Vision Transformer
ArXiv, 2023 Accepted for publication at MIDL 2024, 17 pages, 6 ...
Dahan, Simon +3 more
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Variable-Rate Deep Image Compression With Vision Transformers
IEEE Access, 2022 Recently, vision transformers have been applied in many computer vision problems due to its long-range learning ability. However, it has not been throughly explored in image compression.
Binglin Li, Jie Liang, Jingning Han
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, 2022 Human vision possesses a special type of visual processing systems called peripheral vision. Partitioning the entire visual field into multiple contour regions based on the distance to the center of our gaze, the peripheral vision provides us the ability to perceive various visual features at different regions.
Min, Juhong +3 more
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EnViTSA: Ensemble of Vision Transformer with SpecAugment for Acoustic Event Classification
Sensors, 2023 Recent successes in deep learning have inspired researchers to apply deep neural networks to Acoustic Event Classification (AEC). While deep learning methods can train effective AEC models, they are susceptible to overfitting due to the models’ high ...
Kian Ming Lim +3 more
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Through-Ice Acoustic Source Tracking Using Vision Transformers with Ordinal Classification
Sensors, 2022 Ice environments pose challenges for conventional underwater acoustic localization techniques due to their multipath and non-linear nature. In this paper, we compare different deep learning networks, such as Transformers, Convolutional Neural Networks ...
Steven Whitaker +3 more
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Language Modeling with Deep Transformers
, 2019 We explore deep autoregressive Transformer models in language modeling for speech recognition. We focus on two aspects. First, we revisit Transformer model configurations specifically for language modeling. We show that well configured Transformer models
Irie, Kazuki +3 more
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Transformer Networks for Trajectory Forecasting
, 2020 Most recent successes on forecasting the people motion are based on LSTM models and all most recent progress has been achieved by modelling the social interaction among people and the people interaction with the scene.
Cristani, Marco +3 more
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Artwork Style Recognition Using Vision Transformers and MLP Mixer
Technologies, 2021 Through the extensive study of transformers, attention mechanisms have emerged as potentially more powerful than sequential recurrent processing and convolution.
Lazaros Alexios Iliadis +4 more
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A Provable Defense for Deep Residual Networks
, 2019 We present a training system, which can provably defend significantly larger neural networks than previously possible, including ResNet-34 and DenseNet-100. Our approach is based on differentiable abstract interpretation and introduces two novel concepts:
Mirman, Matthew +2 more
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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.
Schaerf, Ludovica +2 more
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