Results 101 to 110 of about 1,817,676 (247)

Semantic Retrieval and Automatic Annotation: Linear Transformations, Correlation and Semantic Spaces

, 2010
This paper proposes a new technique for auto-annotation and semantic retrieval based upon the idea of linearly mapping an image feature space to a keyword space.
Lewis, Paul, Hare, Jonathan
core   +1 more source

Integrated design-sense-plan architecture for autonomous geometric-semantic mapping with UAVs. [PDF]

Front Robot AI, 2022
Pimentel de Figueiredo R, Le Fevre Sejersen J, Grimm Hansen J, Brandão M.   +3 more
europepmc   +1 more source

SemanticST: A Scalable Multi‐Contextual Graph Learning Framework for Uncovering Spatial Niches and Robust Multi‐Sample Integration in Spatial Transcriptomics

Advanced Science, EarlyView.
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi, Ahmadreza Argha, Nona Farbehi, Ivan Bakhshayeshi, Thantrira Porntaveetus, Youqiong Ye, Nigel H. Lovell, Hamid Alinejad‐Rokny   +7 more
wiley   +1 more source

A community based approach for managing ontology alignments [PDF]

, 2008
The Semantic Web is rapidly becoming a defacto distributed repository for semantically represented data, thus leveraging on the added on value of the network effect.
Correndo, Gianluca, Alani, Harith, Smart, Paul R   +2 more
core   +1 more source

Monocular camera and laser based semantic mapping system with temporal-spatial data association for indoor mobile robots. [PDF]

Multimed Tools Appl, 2023
Song X, Zhijiang Z, Liang X, Huaidong Z.
europepmc   +1 more source

Deep Learning‐Driven Discovery and Engineering of an Efficient PETase for Depolymerization and Detoxification of PET Microplastics Under Physiological Conditions

Advanced Science, EarlyView.
A deep learning–driven pipeline mining 246 million protein sequences uncovers AhPETase, an evolutionarily distinct PET hydrolase. Engineered variant AhPETaseM1 degrades post‐consumer PET microplastics under physiological conditions and reverses microplasticinduced cytotoxicity in human lung and colon cells, establishing enzymatic microplastic ...
Yuxuan Wang, Shijie He, Yuheng Chang, Sheng Mao, Jianan Canal Li, Binbin Chen, Hongxun Gao, Mingchun Xu, Chenxu Liu, Yajie Wang   +9 more
wiley   +1 more source

Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes

Advanced Science, EarlyView.
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley   +1 more source

Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection. [PDF]

Sensors (Basel), 2022
Schischmanow A, Dahlke D, Baumbach D, Ernst I, Linkiewicz M.   +4 more
europepmc   +1 more source

A Site‐Aware Representation Learning Framework For Unified Molecular Interaction Modeling and Generative Design

Advanced Science, EarlyView.
MolDBG is a site‐aware, sequence‐only framework that unifies drug‐target affinity prediction, binding‐site identification, and affinity‐conditioned molecular generation for structured proteins. Guided by multi‐task binding‐site supervision, it aligns interaction‐critical residues before learning drug‐target representations and simultaneously infers ...
Gang Luo, Qianqian Zhang, Chenhao Wang, Zhiheng Yi, Alex Jinpeng Wang, Jing Tang, Min Li   +6 more
wiley   +1 more source

Spatial Concepts-Based Prompts With Large Language Models for Robot Action Planning

IEEE Access
Daily life instructions often include contextual cues related not to the object itself, but to its surrounding environment (e.g., objects placed around the target).
Shoichi Hasegawa, Yoshinobu Hagiwara, Akira Taniguchi, Lotfi El Hafi, Tadahiro Taniguchi   +4 more
doaj   +1 more source