Results 141 to 150 of about 102,109 (257)

Automatic annotation for weakly supervised learning of detectors

, 2012
PhDObject detection in images and action detection in videos are among the most widely studied computer vision problems, with applications in consumer photography, surveillance, and automatic media tagging. Typically, these standard detectors are fully
Siva, Parthipan
core  

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

Advanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

PhosSight: A Unified Deep Learning Framework Boosting and Accelerating Phosphoproteome Identification to Enable Biological Discoveries

Advanced Science, EarlyView.
PhosSight is a unified deep‐learning framework for phosphoproteome identification, featured by a phosphorylation‐aware detectability predictor. It improves identification sensitivity in DDA through deep re‐localization and rescoring, accelerates DIA searches by detectability‐guided spectral library pruning, and expands phosphoproteome coverage to ...
Ben Wang, Zhiyuan Cheng, Chengying She, Hongwei Zhao, Jiahui Zhang, Lin Lv, Zhihao Yan, Hongwen Zhu, Lizhuang Liu, Yan Fu, Xinpei Yi   +10 more
wiley   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Shifting to machine supervision: annotation-efficient semi and self-supervised learning for automatic medical image segmentation and classification

Scientific Reports
Advancements in clinical treatment are increasingly constrained by the limitations of supervised learning techniques, which depend heavily on large volumes of annotated data.
Pranav Singh, Raviteja Chukkapalli, Shravan Chaudhari, Luoyao Chen, Mei Chen, Jinqian Pan, Craig Smuda, Jacopo Cirrone   +7 more
doaj   +1 more source

SSC-EKE: Semi-Supervised Classification with Extensive Knowledge Exploitation. [PDF]

Inf Sci (N Y), 2018
Qian P, Xi C, Xu M, Jiang Y, Su KH, Wang S, Muzic RF.   +6 more
europepmc   +1 more source

Deep Semi-supervised Learning for Time Series Classification

422428While deep semi-supervised learning has gained much attention in computer vision, limited research exists on its applicability in the time series domain.
Rügamer, David, Bischl, Bernd, Goschenhofer, Jann, Wagner, Moritz, Thomas, Janek, Hvingelby, Rasmus   +5 more
core   +1 more source

Heat Shock Protein 90: From Molecular Chaperone Function to Therapeutic Targeting in Malignancies

Advanced Science, EarlyView.
In this review, an integrated conceptual framework linking HSP90's molecular chaperone functions to its pathological roles in cancer is proposed. HSP90 serves as a central node that integrates oncogenic signaling, buffers proteotoxic stress, maintains cancer stem cell plasticity, and shapes tumor‐immune interactions, all of which converge to drive ...
Beibei Zhang, Xinxin Zou, Jiansong Zhou, Qinmiao Sun, Dahua Chen   +4 more
wiley   +1 more source

Entropy Decoding the Fundamental Law of Phase Competition in Glass Formation

Advanced Science, EarlyView.
We validate the integration of intermetallic and eutectic phases as initial phases for composition design. The phase competition mechanism in glass formation is quantitatively clarified based on the melting entropy of competing phases. Glass‐forming ability is modulated by tuning phase competition via the melting entropy of initial phases.
Benke Huo, Zhengqing Cai, Bingtao Wang, Zhenqiang Song, Shi‐Dong Feng, Zijing Li, Xingjun Liu, Li‐Min Wang   +7 more
wiley   +1 more source

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

Advanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi, Minying Low, Peng Xiu, Kresten Lindorff‐Larsen, Yong Wang   +4 more
wiley   +1 more source