Results 121 to 130 of about 546,017 (306)
A Synovium‐on‐Chip Platform to Study Multicellular Interactions in Arthritis
The Synovium‐on‐Chip comprises a thin microporous PDMS membrane to support co‐culture of fibroblast‐like synoviocytes (FLS), THP‐1‐derived macrophages, and endothelial cells, enabling real‐time analysis of synovial‐vascular interactions. FLS migration through the pores drives endothelial remodeling, while TNF‐α stimulation induces robust inflammatory ...
Laurens R. Spoelstra +8 more
wiley +1 more source
Self supervised learning based emotion recognition using physiological signals
IntroductionThe significant role of emotional recognition in the field of human-machine interaction has garnered the attention of many researchers. Emotion recognition based on physiological signals can objectively reflect the most authentic emotional ...
Min Zhang, YanLi Cui
doaj +1 more source
Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring [PDF]
Omiros Pantazis +3 more
openalex +1 more source
Gated Self-supervised Learning for Improving Supervised Learning
In past research on self-supervised learning for image classification, the use of rotation as an augmentation has been common. However, relying solely on rotation as a self-supervised transformation can limit the ability of the model to learn rich features from the data.
Fuadi, Erland Hilman +3 more
openaire +2 more sources
This review explores how alternative invertebrate and small‐vertebrate models advance the evaluation of nanomaterials across medicine and environmental science. By bridging cellular and organismal levels, these models enable integrated assessment of toxicity, biodistribution, and therapeutic performance.
Marie Celine Lefevre +3 more
wiley +1 more source
Ladder Siamese Network: a Method and Insights for Multi-level Self-Supervised Learning [PDF]
Ryota Yoshihashi +5 more
openalex +1 more source
Self-supervised video representation learning
Videos are an appealing source of data to train computer vision models. There exist almost infinite supplies of videos online, but exhaustive manual annotation is infeasible. The goal of this thesis is to learn strong video representations efficiently via self-supervised learning: a method that learns from the data rather than human annotations.
openaire +2 more sources
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Towards Precise and Robust Hippocampus Segmentation using Self-Supervised Contrastive Learning
Kassymzhomart Kunanbayev +3 more
openalex +1 more source
Cold-start Active Learning through Self-supervised Language Modeling [PDF]
Michelle Yuan +2 more
openalex +1 more source

