What Does a Language-And-Vision Transformer See: The Impact of Semantic Information on Visual Representations. [PDF]
Ilinykh N, Dobnik S.
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Semantic Information Elicitation
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This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando +4 more
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LVID-SLAM: A Lightweight Visual-Inertial SLAM for Dynamic Scenes Based on Semantic Information. [PDF]
Wang S +5 more
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Three-Dimensional Model of the Moon with Semantic Information of Craters Based on Chang'e Data. [PDF]
Lu Y +5 more
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Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
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Asymmetric representation of symmetric semantic information in the human brain. [PDF]
Wang J +5 more
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Shared neural codes for visual and semantic information about familiar faces in a common representational space. [PDF]
Visconti di Oleggio Castello M +2 more
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Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
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Video map: A realtime orthographic geo-image considering DEM and semantic information. [PDF]
Zhang X, Li X, Ren S, Liu M, Yang S.
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