Results 101 to 110 of about 6,131,436 (285)

Investigating Contrastive Pair Learning’s Frontiers in Supervised, Semisupervised, and Self-Supervised Learning

Journal of Imaging
In recent years, contrastive learning has been a highly favored method for self-supervised representation learning, which significantly improves the unsupervised training of deep image models. Self-supervised learning is a subset of unsupervised learning
Bihi Sabiri, Amal Khtira, Bouchra El Asri, Maryem Rhanoui   +3 more
doaj   +1 more source

When Low Rank Representation Based Hyperspectral Imagery Classification Meets Segmented Stacked Denoising Auto-Encoder Based Spatial-Spectral Feature

Remote Sensing, 2018
When confronted with limited labelled samples, most studies adopt an unsupervised feature learning scheme and incorporate the extracted features into a traditional classifier (e.g., support vector machine, SVM) to deal with hyperspectral imagery ...
Cong Wang, Lei Zhang, Wei Wei, Yanning Zhang   +3 more
doaj   +1 more source

Unsupervised Hierarchical Symbolic Regression for Interpretable Property Modeling in Complex Multi‐Variable Systems

Advanced Science, EarlyView.
UHSR translates complex chemical behavior into clear and explainable equations. Applied to thin‐layer chromatography, it automatically uncovers the mathematical rules linking a molecule's structure to its polarity. This approach matches the accuracy of advanced AI while providing interpretable results, earning greater trust from chemists. The method is
Siyu Lou, Chengchun Liu, Dongxiao Zhang, Yuntian Chen, Fanyang Mo   +4 more
wiley   +1 more source

Anomaly Detection in Blockchain Networks Using Unsupervised Learning: A Survey

Algorithms
In decentralized systems, the quest for heightened security and integrity within blockchain networks becomes an issue. This survey investigates anomaly detection techniques in blockchain ecosystems through the lens of unsupervised learning, delving into ...
Christos Cholevas, Eftychia Angeli, Zacharoula Sereti, Emmanouil Mavrikos, George E. Tsekouras   +4 more
doaj   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Cell Segmentation Without Annotation by Unsupervised Domain Adaptation Based on Cooperative Self-Learning

IEEE Access
Semantic cell segmentation from microscopic images is essential for the quantitative evaluation of cell morphology. Although supervised deep-learning-based models offer accurate segmentation, their performance degrades for unknown cell types.
Shintaro Miyaki, Takashi Morikura, Shori Nishimoto, Yuta Tokuoka, Takahiro G. Yamada, Akira Funahashi   +5 more
doaj   +1 more source

Loss of VMP1 Impairs Tight Junction Recycling and Aggravates Intestinal Barrier Dysfunction in Inflammatory Bowel Disease

Advanced Science, EarlyView.
This study identifies vacuole membrane protein 1 (VMP1) as a critical regulator of intestinal epithelial barrier homeostasis. VMP1 facilitates the recruitment of CORO1C to late endosomes, supporting Retromer‐mediated recycling of the tight junction protein Occludin.
Jiawei Zhao, Jianjun Zou, Chen Zhou, Yingui Wang, Yiman Liu, Yanqing Zhou, Yuxiang Wang, Xinyu Zhang, Huishu Yang, Hongjie Yin, Dongsheng Bai, Yue Zhao, Na Lu   +12 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model

Advanced Science, EarlyView.
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen, Jingrui Zhong, Xiaochun Zhang, Jingke Chen, Lin Guo, Xiaoliang Xiong, Xiaonan Zhang, Xiangyu Liu, Bailong Xiao, Boxue Tian   +9 more
wiley   +1 more source

ALKBH3 m1A Demethylase Deficiency Reduces Alzheimer's Amyloid‐β Pathology

Advanced Science, EarlyView.
This study identifies that ALKBH3‐driven m1A demethylation orchestrates Alzheimer's disease progression by disrupting mitochondrial and synaptic homeostasis. This epitranscriptomic mechanism suppresses PINK1‐mediated mitophagy via m1A erasure, leading to mitochondrial dysfunction, oxidative stress, elevated Aβ production, and impaired microglial ...
Yueyang Li, Sifei Yu, Kaidong Lu, Yujie Zhang, Mingjie Dong, Yan Peng, Liang Xue, Waleed Alam, Yuxuan Shui, Yi Zhou, Wuyunhan Ma, Meng Bao, Peiming Li, Peiyi Luo, Tiezhan Lu, Jiajia Li, Kang Zhang, Yuying Wang, Shuchen Yang, Nuoya Yin, Francesco Faiola, Zilong Gao, Jingfeng Zhou, Fei Zhao, Yali He, Magdalena J. Koziol   +25 more
wiley   +1 more source