Results 51 to 60 of about 24,887 (267)
Frontiers in Artificial IntelligenceEfficient waste management is crucial for urban environments to maintain cleanliness, reduce environmental impact, and optimize resource allocation. Traditional waste collection systems often rely on scheduled pickups or manual inspections, leading to ...
Parakram Singh Tanwer +4 more
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IEEE Access, 2023 Traditionally, the success of the Transformer has been attributed to its token mixer, particularly the self-attention mechanism. However, recent studies suggest that replacing such attention-based token mixer with alternative techniques can yield ...
Dongwook Yang, Seung-Woo Seo
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Advanced Engineering Materials, EarlyView.This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
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Accepted to ECCV2024. Project website: https://jiawei-yang.github.io/DenoisingViT/
Jiawei Yang 0002 +8 more
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Vision Language Transformers: A Survey
CoRR, 2023 Vision language tasks, such as answering questions about or generating captions that describe an image, are difficult tasks for computers to perform. A relatively recent body of research has adapted the pretrained transformer architecture introduced in \citet{vaswani2017attention} to vision language modeling.
Clayton Fields, Casey Kennington
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The PRIMA Thesaurus for Materials Science and Engineering
Advanced Engineering Materials, EarlyView.The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa +8 more
wiley +1 more source
Interpretability-Aware Vision Transformer
CoRR, 2023 Vision Transformers (ViTs) have become prominent models for solving various vision tasks. However, the interpretability of ViTs has not kept pace with their promising performance. While there has been a surge of interest in developing {\it post hoc} solutions to explain ViTs' outputs, these methods do not generalize to different downstream tasks and ...
Yao Qiang +3 more
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Advanced Engineering Materials, EarlyView.Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)Vision Transformers (ViTs) have recently become the state-of-the-art across many computer vision tasks. In contrast to convolutional networks (CNNs), ViTs enable global information sharing even within shallow layers of a network, i.e., among high-resolution features. However, this perk was later overlooked with the success of pyramid architectures such
Jongwoo Park 0003 +5 more
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IET Image ProcessingThe Swin‐Transformer is a variant of the Vision Transformer, which constructs a hierarchical Transformer that computes representations with shifted windows and window multi‐head self‐attention.
Yixuan Xu +3 more
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