Results 81 to 90 of about 120,140 (335)

Emerging insights into CC and CXC chemokines and their receptors in Mycobacterium tuberculosis infection

FEBS Open Bio, EarlyView.
The dual roles of CC and CXC chemokines in distinguishing active, latent, and subclinical tuberculosis were reviewed, along with an evaluation of their potential as diagnostic biomarkers and therapeutic targets to advance precision medicine in tuberculosis management. The graphical abstract was generated with AI assistance (Gemini 3.0).
Xuying Yin, Dangsheng Xiao, Jiezuan Yang
wiley   +1 more source

Dual Contrastive Learning Model Based Background Debiasing in SAR ATR

Shuju Caiji Yu Chuli
Contrastive learning， as a self-supervised approach， enables the extraction of target representations from unlabeled SAR images， serving as a critical technique for automatic target recognition （ATR） in SAR.
ZHANG Wenqing, WANG Jing, HUANG Xueqin, TIAN Sirui, HE Cheng, ZHANG Jingdong, LI Hongtao   +6 more
doaj   +1 more source

GFCNet: Contrastive Learning Network with Geography Feature Space Joint Negative Sample Correction for Land Cover Classification

Remote Sensing, 2023
With the continuous improvement in the volume and spatial resolution of remote sensing images, the self-supervised contrastive learning paradigm driven by a large amount of unlabeled data is expected to be a promising solution for large-scale land cover ...
Zhaoyang Zhang, Wenxuan Jing, Haifeng Li, Chao Tao, Yunsheng Zhang   +4 more
doaj   +1 more source

Prototypical Graph Contrastive Learning

CoRR, 2021
Graph-level representations are critical in various real-world applications, such as predicting the properties of molecules. But in practice, precise graph annotations are generally very expensive and time-consuming. To address this issue, graph contrastive learning constructs instance discrimination task which pulls together positive pairs ...
Shuai Lin, Pan Zhou 0002, Zi-Yuan Hu, Shuojia Wang, Ruihui Zhao, Yefeng Zheng 0001, Liang Lin, Eric P. Xing, Xiaodan Liang   +8 more
openaire   +2 more sources

Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo [PDF]

, 2022
Chaoning Zhang, Kang Zhang, Trung X. Pham, Axi Niu, Zhinan Qiao, Chang D. Yoo, In So Kweon   +6 more
openalex   +1 more source

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Metadata Enriched Multi-Instance Contrastive Learning for High-Quality Facial Skin Visual Representations

Applied Artificial Intelligence
Utilizing self-supervised learning to learn meaningful representations from unlabeled data can be a cost-effective strategy, particularly in medical domains where expert labeling incurs high costs.
Jihyo Kim, Sungchul Kim, Seungwon Seo, Bumsoo Kim, Daejeong Mun, Hoonjae Lee, Sangheum Hwang   +6 more
doaj   +1 more source

Deep Metric Learning via Lifted Structured Feature Embedding

, 2015
Learning the distance metric between pairs of examples is of great importance for learning and visual recognition. With the remarkable success from the state of the art convolutional neural networks, recent works have shown promising results on ...
Jegelka, Stefanie, Savarese, Silvio, Song, Hyun Oh, Xiang, Yu   +3 more
core   +1 more source

Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning

CoRR
Despite its empirical success, the theoretical foundations of self-supervised contrastive learning (CL) are not yet fully established. In this work, we address this gap by showing that standard CL objectives implicitly approximate a supervised variant we call the negatives-only supervised contrastive loss (NSCL), which excludes same-class contrasts. We
Achleshwar Luthra, Tianbao Yang, Tomer Galanti   +2 more
openaire   +2 more sources

Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer

Aging and Cancer, EarlyView.
Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss, Alexis C. Wardell, Allison M. Deal, Kirsten A. Nyrop, Allison Ross, Yara G. Abdou, Jeffrey D. Aldrich, Lisa A. Cary, E. Claire Dees, Katherine E. Reeder‐Hayes, Emily M. Ray, Natalia Mitin, Denis Tsygankov   +12 more
wiley   +1 more source