Results 71 to 80 of about 24,671,802 (285)

DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification

, 2023
In recent years, multi-view multi-label learning has aroused extensive research enthusiasm. However, multi-view multi-label data in the real world is commonly incomplete due to the uncertain factors of data collection and manual annotation, which means ...
Xu, Yong, Luo, Xiaoling, Huang, Chao, Wu, Zhihao, Liu, Chengliang, Wen, Jie   +5 more
core   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Semantic consistency enhancement and contribution-driven network for partial multi-view incomplete multi-label classification

Journal of King Saud University: Computer and Information Sciences
In recent years, multi-view multi-label learning has garnered considerable attention due to its broad application prospects, such as bioinformatics and medical imaging.
Yishan Jiang, Lian Zhao, Zhixian Jiang, Yinghao Ye, Xiaohuan Lu   +4 more
doaj   +1 more source

Federated Incomplete Multi-View Unsupervised Feature Selection with Fractional Sparsity-Guided Whale Optimization and Tensor Alternating Learning

Fractal and Fractional
With the widespread application of multi-view data across various domains, multi-view unsupervised feature selection (MUFS) has achieved remarkable progress in both feature selection (FS) and missing-view completion.
Yufan Yuan, Wangyu Wu, Chang-An Xu, Weirong Zhang, Chuan Jin   +4 more
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Siamese network with squeeze-attention for incomplete multi-view multi-label classification

Complex & Intelligent Systems
Multi-view multi-label classification (MvMLC) has garnered significant interest because of its ability to handle complex datasets. However, the inherent complexity of real-world data often results in incomplete views and missing labels, which limit the ...
Mengqing Wang, Jiarui Chen, Lian Zhao, Yinghao Ye, Xiaohuan Lu   +4 more
doaj   +1 more source

Multi-view Sample Augumentation for SAR Based onDifferentiable SAR Renderer

Leida xuebao
Synthetic Aperture Radar (SAR) is extensively utilized in civilian and military domains due to its all-weather, all-time monitoring capabilities. In recent years, deep learning has been widely employed to automatically interpret SAR images.
Hecheng JIA, Xinyang PU, Yanni WANG, Shilei FU, Feng XU   +4 more
doaj   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Wave optics optimization with tensor anchor graph joint learning for unbalanced incomplete multi-view unsupervised feature selection

Journal of King Saud University: Computer and Information Sciences
While multi-view unsupervised feature selection (MUFS) has achieved substantial progress, real-world unbalanced and incomplete multi-view data with uneven cross-view missing proportions poses significant challenges.
Yanli Cai, Fuyin Dai, Zhigang Zhang, Kaifan Zhang   +3 more
doaj   +1 more source

Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding

Incomplete multi-view clustering becomes an important research problem, since multi-view data with missing values are ubiquitous in real-world applications.
Chu, Dianhui, Chao, Guoqing, Jiang, Yi
core   +1 more source