Results 21 to 30 of about 172,675 (276)
Machine Learning and Knowledge Extraction, 2023 This study introduces an optimal topology of vision transformers for real-time video action recognition in a cloud-based solution. Although model performance is a key criterion for real-time video analysis use cases, inference latency plays a more ...
Saman Sarraf, Milton Kabia
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Supervised deep learning with vision transformer predicts delirium using limited lead EEG
Scientific Reports, 2023 As many as 80% of critically ill patients develop delirium increasing the need for institutionalization and higher morbidity and mortality. Clinicians detect less than 40% of delirium when using a validated screening tool.
Malissa A. Mulkey +4 more
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, 2021 Vision transformer has achieved competitive performance on a variety of computer vision applications. However, their storage, run-time memory, and computational demands are hindering the deployment to mobile devices. Here we present a vision transformer pruning approach, which identifies the impacts of dimensions in each layer of transformer and then ...
Zhu, Mingjian, Tang, Yehui, Han, Kai
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International Journal of Computer Vision, 2023 We attempt to reduce the computational costs in vision transformers (ViTs), which increase quadratically in the token number. We present a novel training paradigm that trains only one ViT model at a time, but is capable of providing improved image recognition performance with various computational costs. Here, the trained ViT model, termed super vision
Lin, Mingbao +5 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
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Distinguishing Malicious Drones Using Vision Transformer
AI, 2022 Drones are commonly used in numerous applications, such as surveillance, navigation, spraying pesticides in autonomous agricultural systems, various military services, etc., due to their variable sizes and workloads.
Sonain Jamil +2 more
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Vision Transformer in Industrial Visual Inspection
Applied Sciences, 2022 Artificial intelligence as an approach to visual inspection in industrial applications has been considered for decades. Recent successes, driven by advances in deep learning, present a potential paradigm shift and have the potential to facilitate an ...
Nils Hütten +2 more
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RT-ViT: Real-Time Monocular Depth Estimation Using Lightweight Vision Transformers
Sensors, 2022 The latest research in computer vision highlighted the effectiveness of the vision transformers (ViT) in performing several computer vision tasks; they can efficiently understand and process the image globally unlike the convolution which processes the ...
Hatem Ibrahem +2 more
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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.
Paul, Sayak, Chen, Pin-Yu
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Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review
BMC Medical Imaging, 2023 Background Vision transformer-based methods are advancing the field of medical artificial intelligence and cancer imaging, including lung cancer applications.
Hazrat Ali, Farida Mohsen, Zubair Shah
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