Results 111 to 120 of about 11,177,407 (275)

Retrieval-enriched zero-shot image classification in low-resource domains

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Low-resource domains, characterized by scarce data and annotations, present significant challenges for language and visual understanding tasks, with the latter much under-explored in the literature. Recent advancements in Vision-Language Models (VLM) have shown promising results in high-resource domains but fall short in low-resource concepts that are ...
Nicola Dall'Asen, Yiming Wang, Enrico Fini, Elisa Ricci   +3 more
openaire   +5 more sources

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

A Single‐Cell Transcriptomic Atlas of the Ovine Rumen Microbiome Characterizes Lineage‐Specific Metabolic Shifts Associated with Host Heat Tolerance

Advanced Science, EarlyView.
An optimized single‐cell transcriptomic framework profiles over 60 000 cells to map the ovine rumen microbiome, partitioning the ecosystem into seven cross‐species functional clusters. In heat‐resistant hosts, a lineage‐specific metabolic shift in Anaerovibrio lipolyticus toward a highly glycolytic phenotype contributes to a “nutritional sparing ...
Sanbao Zhang, Qinyang Jiang, Junjie Ma, Jianwei Zou, Fan Wang, Feifei Lv, Yanna Huang, Yongcheng Wang, Ziye Xu   +8 more
wiley   +1 more source

Prompt-SAM: A Vision-Language and SAM based Hybrid Framework for Prompt-Augmented Zero-Shot Segmentation

Human-Centric Intelligent Systems
Recent advancements in deep learning have greatly improved computer vision tasks like object detection, image classification, and segmentation. Despite these successes, traditional supervised learning methods still depend on large annotated datasets ...
Uma Gurav, Sanket Jadhav
doaj   +1 more source

Vision-language zero-shot models for radiographic image classification: A systematic review

Machine Learning with Applications
Zero-shot Vision-Language Models (VLMs) link visual and textual features, enabling generalization to unseen domains, making them promising for radiographic diagnosis, though clinical adoption is limited.This systematic review examines zero-shot VLMs ...
Ana Guerrero-Tamayo, Ibon Oleagordia-Ruiz, Begonya Garcia-Zapirain   +2 more
doaj   +1 more source

AI‐Assisted Digital Single‐Molecule Activity Tracker for Decoupling Intrinsic Heterogeneity from Photo‐Oxidative Damage in High‐Photon‐Flux Enzymology

Advanced Science, EarlyView.
Employing a digital single‐molecule activity tracker (dSMAT), this research demonstrates that high‐photon‐flux irradiation drives progressive oxidative scarring in polymerases. Unlike simple thermal denaturation, real‐time kinetic tracking dynamically visualizes enzymes degrading into multiple impaired subpopulations.
Anran Zheng, Qi Yang, Jinze Li, Fuqiang Ma, Xuefeng Wang, Zhen Guo, Chuanyu Li, Dongshu Li, Jia Yao, Zhiqi Zhang, Wei Zhang, Lianqun Zhou   +11 more
wiley   +1 more source

Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classification

, 2016
International audienceThis paper addresses the task of zero-shot image classification. The key contribution of the proposed approach is to control the semantic embedding of images – one of the main ingredients of zero-shot learning – by formulating it as
Herbin, Stéphane, Jurie, Frédéric, Bucher, Maxime   +2 more
core   +1 more source

Vision-language model approach for few-shot learning of attention deficit hyperactivity disorder using EEG connectivity-based featured images

Machine Learning: Science and Technology
Traditional medical diagnosis approaches have predominantly relied on single-modality analysis, limiting clinicians to interpreting isolated data streams such as images or time series.
Mehmet Sergen Catal, Abdurrahman Gumus, Ozlem Karabiber Cura, Ocan Aydin, Mehmet Zübeyir Ünlü   +4 more
doaj   +1 more source

Molecular and Cellular Hallmarks of Age‐Related Vestibular Hair Cell Degeneration

Advanced Science, EarlyView.
This study utilizes single‐cell RNA‐seq transcriptomes, advanced imaging, and electrophysiology to examine universal and cell‐type‐specific aging signatures of vestibular hair cells. The study shows that impaired hair bundle function is a key driver of age‐related vestibular dysfunction.
Samadhi Kulasooriya, Huizhan Liu, Sarath Vijayakumar, Celia Bloom, Zhenhang Xu, Shu Tu, Benjamin J. Borgmeier, Mi Zhou, Litao Tao, Bechara Kachar, David Z. He   +10 more
wiley   +1 more source

A few-shot diabetes foot ulcer image classification method based on deep ResNet and transfer learning

Scientific Reports
Diabetes foot ulcer (DFU) is one of the common complications of diabetes patients, which may lead to infection, necrosis and even amputation. Therefore, early diagnosis, classification of severity and related treatment are crucial for the patients ...
Cheng Wang, Zhen Yu, Zhou Long, Hui Zhao, Zhenwei Wang   +4 more
doaj   +1 more source