Results 31 to 40 of about 96,008 (322)
Identifying the role of vision transformer for skin cancer—A scoping review
Frontiers in Artificial Intelligence, 2023 IntroductionDetecting and accurately diagnosing early melanocytic lesions is challenging due to extensive intra- and inter-observer variabilities. Dermoscopy images are widely used to identify and study skin cancer, but the blurred boundaries between ...
Sulaiman Khan, Hazrat Ali, Zubair Shah
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Vision Transformers Are Robust Learners
Proceedings of the AAAI Conference on Artificial Intelligence, 2022 Transformers, composed of multiple self-attention layers, hold strong promises toward a generic learning primitive applicable to different data modalities, including the recent breakthroughs in computer vision achieving state-of-the-art (SOTA) standard accuracy. What remains largely unexplored is their robustness evaluation and attribution.
Sayak Paul, Pin-Yu Chen
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Adjustment of model parameters to estimate distribution transformers remaining lifespan [PDF]
, 2018 Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the ...
Gotay Sardiñas, Jorge +3 more
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The role of intelligent systems in delivering the smart grid [PDF]
, 2010 The development of "smart" or "intelligent" energy networks has been proposed by both EPRI's IntelliGrid initiative and the European SmartGrids Technology Platform as a key step in meeting our future energy needs.
Catterson, Victoria +2 more
core +1 more source
Re-Introducing BN Into Transformers for Vision Tasks
IEEE Access, 2023 In recent years, Transformer-based models have exhibited significant advancements over previous models in natural language processing and vision tasks. This powerful methodology has also been extended to the 3D point cloud domain, where it can mitigate ...
Xue-Song Tang, Xian-Lin Xie
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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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Voltage regulation considerations for the design of hybrid distribution transformers [PDF]
, 2014 The future substation depends on finding a way to mitigate the effects of the drawbacks of the conventional legacy by employing the efficiency of the solid state switches [1].
Alqarni, M, Darwish, M, Radi, MA
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Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers
CAAI Artificial Intelligence Research, 2023 Most polyp segmentation methods use convolutional neural networks (CNNs) as their backbone, leading to two key issues when exchanging information between the encoder and decoder: (1) taking into account the differences in contribution between different ...
Bo Dong +5 more
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BUViTNet: Breast Ultrasound Detection via Vision Transformers
Diagnostics, 2022 Convolutional neural networks (CNNs) have enhanced ultrasound image-based early breast cancer detection. Vision transformers (ViTs) have recently surpassed CNNs as the most effective method for natural image analysis. ViTs have proven their capability of
Gelan Ayana, Se-woon Choe
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Areas of Attention for Image Captioning [PDF]
, 2016 We propose "Areas of Attention", a novel attention-based model for automatic image captioning. Our approach models the dependencies between image regions, caption words, and the state of an RNN language model, using three pairwise interactions.
Lucas, Thomas +3 more
core +5 more sources