Results 71 to 80 of about 5,390 (262)

Masked Siamese Networks for Label-Efficient Learning

, 2022
We propose Masked Siamese Networks (MSN), a self-supervised learning framework for learning image representations. Our approach matches the representation of an image view containing randomly masked patches to the representation of the original unmasked image.
Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael G. Rabbat, Nicolas Ballas   +8 more
openaire   +2 more sources

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

Interactive Instance Annotation with Siamese Networks

CoRR
Annotating instance masks is time-consuming and labor-intensive. A promising solution is to predict contours using a deep learning model and then allow users to refine them. However, most existing methods focus on in-domain scenarios, limiting their effectiveness for cross-domain annotation tasks.
Xiang Xu, Ruotong Li, Mengjun Yi, Baile Xu, Furao Shen, Jian Zhao 0013   +5 more
openaire   +2 more sources

Partial Discharge Diagnosis With Siamese Fusion Network

IEEE Access, 2022
Partial discharge is a common fault type in the operation of power equipment. Recently, deep learning methods have shown great potential in partial discharge (PD) diagnosis. These methods construct a fitting relationship between input and output with mass training samples.
Zhihong Huang, Wei Huang, Xianyong Xu, Jian Xiao   +3 more
openaire   +2 more sources

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

AL-MRIS: An Active Learning-Based Multipath Residual Involution Siamese Network for Few-Shot Hyperspectral Image Classification

Remote Sensing
In hyperspectral image (HSI) classification scenarios, deep learning-based methods have achieved excellent classification performance, but often rely on large-scale training datasets to ensure accuracy. However, in practical applications, the acquisition
Jinghui Yang, Jia Qin, Jinxi Qian, Anqi Li, Liguo Wang   +4 more
doaj   +1 more source

Two Routes to Land: Genomic Underpinnings of Parallel Aerial Egg Deposition in Aquatic Old‐World Pila and New‐World Pomacea (Ampullariidae)

Advanced Science, EarlyView.
Comparative genomics of Gondwana‐diverged Pila and Pomacea reveals parallel evolution of aerial oviposition. Convergent chromosomal rearrangements reshape regulatory landscapes within topologically associating domains. Lineage‐specific gene family expansions and viral‐derived perivitelline proteins (PV1) underpin desiccation resistance.
Yufei Zhou, Huawei Mu, Xueying Nie, Yue Gao, Hui Wang, Ling Fang, Tiangang Luan, Monthon Ganmanee, Jian‐Wen Qiu, Jin Sun, Jack Chi‐Ho Ip   +10 more
wiley   +1 more source

A Siamese deep learning framework for efficient hardware Trojan detection using power side-channel data

Scientific Reports
Hardware Trojans (HTs) are hidden threats embedded in the circuitry of integrated circuits (ICs), enabling unauthorized access, data theft, operational disruptions, or even physical harm.
Abdurrahman Nasr, Khalil Mohamed, Ayman Elshenawy, Mohamed Zaki   +3 more
doaj   +1 more source

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

Infrared Multi-Pedestrian Tracking in Vertical View via Siamese Convolution Network

IEEE Access, 2019
Target tracking has become one of the research hotspots in the field of computer vision in recent years. In this paper, a new intelligent algorithm of infrared multi-pedestrian tracking in vertical view is proposed.
Guojiang Shen, Linfeng Zhu, Jihan Lou, Si Shen, Zhi Liu, Longfeng Tang   +5 more
doaj   +1 more source