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Fault Diagnosis of Bearings with Small Sample Size Using Improved Capsule Network and Siamese Neural Network [PDF]
SensorsThis paper addresses the challenges of low accuracy and long transfer learning time in small-sample bearing fault diagnosis, which are often caused by limited samples, high noise levels, and poor feature extraction.
Jarula Yasenjiang +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Deep learning (DL) exhibits commendable performance in hyperspectral image (HSI) classification because of its powerful feature expression ability. Siamese neural network further improves the performance of DL models by learning similarities within-class
Zhaohui Xue +3 more
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Automated Bone Marrow Cell Classification for Haematological Disease Diagnosis Using Siamese Neural Network [PDF]
Diagnostics, 2022 The critical structure and nature of different bone marrow cells which form a base in the diagnosis of haematological ailments requires a high-grade classification which is a very prolonged approach and accounts for human error if performed manually ...
Balasundaram Ananthakrishnan +5 more
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IEEE Access, 2021 In order to solve the problems of unbalanced sample data and the lack of consideration of temporal information in existing Siamese-based trackers, this paper proposes a Siamese recurrent neural network and region proposal network (Siamese R-RPN), which ...
Xuechen Zhao, Yaoming Liu, Guang Han
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A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments [PDF]
Nature Communications, 2022 Here, the authors present SemiBin, a siamese deep neural network framework that incorporates information from reference genomes, able to extract better metagenome-assembled genomes (MAGs) in several host-associated and environmental habitats.
Shaojun Pan +3 more
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A Lightweight Siamese Neural Network for Building Change Detection Using Remote Sensing Images
Remote Sensing, 2023 Building change detection (BuCD) can offer fundamental data for applications such as urban planning and identifying illegally-built new buildings. With the development of deep neural network-based approaches, BuCD using high-spatial-resolution remote ...
Haiping Yang +6 more
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Remote Sensing, 2023 Ship classification using the synthetic aperture radar (SAR) images has a significant role in remote sensing applications. Aiming at the problems of excessive model parameters numbers and high energy consumption in the traditional deep learning methods ...
Xinqiao Jiang +3 more
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Forensic identification using siamese, transfer learning and custom deep learning models [PDF]
Scientific ReportsForensic identification from human skulls plays a crucial role in forensic anthropology, providing critical insights into the determination of sex, ancestry, and other important characteristics of unidentified human remains.
Omer Sevinc +3 more
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A siamese neural network model for phase identification in distribution networks
International Journal of Electrical Power & Energy SystemsDistribution system operators (DSOs) often lack high-quality data on low-voltage distribution networks (LVDNs), including the topology and the phase connection of residential customers. The phase connection is essential for phase balancing assessment and
Dong Liu +3 more
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MASNET: IMPROVE PERFORMANCE OF SIAMESE NETWORKS WITH MUTUAL-ATTENTION FOR REMOTE SENSING CHANGE DETECTION TASKS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Siamese networks are widely used for remote sensing change detection tasks. A vanilla siamese network has two identical feature extraction branches which share weights, these two branches work independently and the feature maps are not fused until about ...
H. Zhou +6 more
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