Results 131 to 140 of about 2,236,896 (335)

Zero-Shot Learning via Category-Specific Visual-Semantic Mapping and Label Refinement

IEEE Transactions on Image Processing, 2019
Zero-shot learning (ZSL) aims to classify a test instance from an unseen category based on the training instances from seen categories in which the gap between seen categories and unseen categories is generally bridged via visual-semantic mapping between
Li Niu, Jianfei Cai, A. Veeraraghavan, Liqing Zhang   +3 more
semanticscholar   +1 more source

Machine‐Learning Decomposition Identifies a Big Two Structure in Human Personality with Distinct Neurocognitive Profiles

Advanced Science, EarlyView.
Using machine learning on a mega‐scale global dataset (n = 1,336,840) reveals a robust personality trait architecture beyond the Big Five. A Big Two model, broadly capturing social engagement and internal mentation, defines a geometric space that links personality to neurocognitive profiles.
Kaixiang Zhuang, Ji Chen, Jinfeng Han, Wei Cheng, Jiang Qiu, Jianfeng Feng, Simon Eickhoff, Deniz Vatansever   +7 more
wiley   +1 more source

Probabilistic Semantic Mapping for Autonomous Driving in Urban Environments. [PDF]

Sensors (Basel), 2023
Zhang H, Venkatramani S, Paz D, Li Q, Xiang H, Christensen HI.   +5 more
europepmc   +1 more source

Semantic Arithmetic Coding Using Synonymous Mappings

Entropy
Recent semantic communication methods explore effective ways to expand the communication paradigm and improve the performance of communication systems. Nonetheless, a common problem with these methods is that the essence of semantics is not explicitly pointed out and directly utilized.
Zijian Liang, Kai Niu, Jin Xu, Ping Zhang   +3 more
openaire   +4 more sources

Farnesyltransferase Deficiency in Cardiomyocytes Initiates Senescence and Contributes to Cardiac Fibrosis

Advanced Science, EarlyView.
Lipid overload suppresses SREBF2‐mediated FNTB expression, leading to defective Lamin A maturation and nuclear envelope instability. This nuclear catastrophe triggers a pro‐fibrotic senescence program in cardiomyocytes. Notably, restoring nuclear integrity via AAV9‐based gene therapy effectively attenuates cardiac remodeling, identifying the ...
Yuxiao Chen, Lian Lou, Xuan Zhang, Lin Yan, Qi Zhang, Wen Shi, Jie Ding, Xu Lin, Rong Jiang, Shuo Liu, Thida Sok, Pengli Wang, Yun Mou, Jie Han, Shenjiang Hu, Xiaogang Guo, Jian Yang   +16 more
wiley   +1 more source

Fine-Grained 3D Modeling and Semantic Mapping of Coral Reefs Using Photogrammetric Computer Vision and Machine Learning. [PDF]

Sensors (Basel), 2023
Zhong J, Li M, Zhang H, Qin J.
europepmc   +1 more source

High‐Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million‐Patient Diabetes Cohort

Advanced Science, EarlyView.
This study generates high‐fidelity synthetic longitudinal records for a million‐patient diabetes cohort, successfully replicating clinical predictive performance. However, deeper analysis reveals algorithmic biases and trajectory inconsistencies that escape standard quality metrics. These findings challenge current validation norms, demonstrating why a
Francisco Ortuño, Víctor M. de la Oliva Roque, Javier‐Ignacio Ramirez‐Lopez, David P. Kreil, Joaquín Dopazo, Carlos Loucera   +5 more
wiley   +1 more source

A Wearable Visually Impaired Assistive System Based on Semantic Vision SLAM for Grasping Operation

Sensors
Because of the absence of visual perception, visually impaired individuals encounter various difficulties in their daily lives. This paper proposes a visual aid system designed specifically for visually impaired individuals, aiming to assist and guide ...
Fei Fei, Sifan Xian, Ruonan Yang, Changcheng Wu, Xiong Lu   +4 more
doaj   +1 more source

Cross-Viewpoint Semantic Mapping: Integrating Human and Robot Perspectives for Improved 3D Semantic Reconstruction. [PDF]

Sensors (Basel), 2023
Kopácsi L, Baffy B, Baranyi G, Skaf J, Sörös G, Szeier S, Lőrincz A, Sonntag D.   +7 more
europepmc   +1 more source

Unveil Fundamental Graph Properties for Neural Architecture Search

Advanced Science, EarlyView.
This paper proposes NASGraph, a graph‐based framework that represents neural architectures as graphs whose structural properties determine performance. By revealing structure–performance relationships, NASGraph enables efficient neural architecture search with significantly reduced computation.
Zhenhan Huang, Tejaswini Pedapati, Pin‐Yu Chen, Chunheng Jiang, Jianxi Gao   +4 more
wiley   +1 more source