Results 91 to 100 of about 3,020,093 (290)

Unsupervised Multi-source Domain Adaptation for Regression

, 2020
International audienceWe consider the problem of unsupervised domain adaptation from multiple sources in a regression setting. We propose in this work an original method to take benefit of different sources using a weighted combination of the sources ...
Antoine de Mathelin, Guillaume Richard, Vayatis, Nicolas, Mougeot, Mathilde, Mathilde Mougeot, Nicolas Vayatis, de Mathelin, Antoine, Georges Hébrail, Hébrail, Georges, Richard, Guillaume   +9 more
core   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Domain‐invariant adversarial learning with conditional distribution alignment for unsupervised domain adaptation

IET Computer Vision, 2020
Unsupervised domain adaption aims to reduce the divergence between the source domain and the target domain. The final objective is to learn domain‐invariant features from both domains that get the minimised expected error on the target domain.
Xingmei Wang, Boxuan Sun, Hongbin Dong
doaj   +1 more source

Co-regularized alignment for unsupervised domain adaptation

, 2019
Deep neural networks, trained with large amount of labeled data, can fail to generalize well when tested with examples from a target domain whose distribution differs from the training data distribution, referred as the source domain. It can be expensive
Freeman, William T., Feris, Rogerio, Wornell, Gregory, Karlinsky, Leonid, Wadhawan, Kahini, Sattigeri, Prasanna, Kumar, Abhishek   +6 more
core  

From Lab to Landscape: Environmental Biohybrid Robotics for Ecological Futures

Advanced Robotics Research, EarlyView.
This Perspective explores environmental biohybrid robotics, integrating living tissues, microorganisms, and insects for operation in real‐world ecosystems. It traces the leap from laboratory experiments to forests, wetlands, and urban environments and discusses key challenges, development pathways, and opportunities for ecological monitoring and ...
Miriam Filippi
wiley   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Unsupervised Domain Adversarial Self-Calibration for Electromyography-Based Gesture Recognition

, 2020
Surface electromyography (sEMG) provides an intuitive and non-invasive interface from which to control machines. However, preserving the myoelectric control system’s performance over multiple days is challenging, due to the transient nature of the ...
Côté-Allard, Ulysse, Glette, Kyrre, Phinyomark, Angkoon, Scheme, Erik, Scheme, Erik J., Gagnon-Turcotte, Gabriel, Gosselin, Benoit, Laviolette, Francois, Côté Allard, Ulysse   +8 more
core   +1 more source

CD9+ B Cells Induce T Follicular Helper Cell Apoptosis to Regulate Germinal Center Regression

Advanced Science, EarlyView.
A unique subset of CD9+ B cells regulates germinal center B (GC‐B) cell regression by inducing T follicular helper (Tfh) cell apoptosis through multiple signaling pathways, such as ALCAM‐CD6. FOXP1 plays a key role in GC‐B cell differentiation. These findings clarify mechanisms of GC degeneration and termination and offer potential targets for adenoid ...
Wenjing Liao, Lijuan Song, Meiqian Xu, Tianhao Liang, Yixuan Chen, Gui Chen, Zaihuan Lin, Huakang Du, Guofei Feng, Zhiming Feng, Qi Zhang, Fan Pan, Saixuan Yang, Xinyin Zhang, Wenxu Peng, Tianlong Li, Zhuoshen Lin, Yabang Chen, Jiayi Liu, Baoxin Peng, Yan Liu, Xing Niu, Ting Li, Chengyu Huang, Ke Mo, Jianlei Xie, Yu Zou, Xiaowen Zhang   +27 more
wiley   +1 more source

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu, Pan Zhang, Shangqian Wu, Hao Sun, Minwei Li, Sophia Tsoka, Zizhang Sheng, Lei Deng   +7 more
wiley   +1 more source

Latent Domain Generation for Unsupervised Domain Adaptation Object Counting

, 2023
Unsupervised cross-domain object counting has recently received great attention in computer vision, which generalizes the model from the source domain to the unlabeled target domain.
Yang, Y., Jun Xu, Xianbin Cao, Cao, X., Xiantong Zhen, Anran Zhang, Yandan Yang, Zhang, A., Shao, L., Ling Shao, Xu, J., Zhen, X.   +11 more
core   +1 more source