Results 21 to 30 of about 26,674 (270)
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
doaj +1 more source
Biomedicines, 2023 Sleep staging is of critical significance to the diagnosis of sleep disorders, and the electroencephalogram (EEG), which is used for monitoring brain activity, is commonly employed in sleep staging.
Yuyang You +3 more
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Siamese tracking network with multi-attention mechanism
Neural Processing Letters, 2023 Abstract Object trackers based on Siamese networks view tracking as a similarity-matching process. However, the correlation operation operates as a local linear matching process, limiting the tracker's ability to capture the intricate nonlinear relationship between the template and search region branches.
Yuzhuo Xu +4 more
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DASTSiam: Spatio‐temporal fusion and discriminative enhancement for Siamese visual tracking
IET Computer Vision, 2023 The use of deep neural networks has revolutionised object tracking tasks, and Siamese trackers have emerged as a prominent technique for this purpose.
Yucheng Huang +6 more
doaj +1 more source
Siamese Instance Search for Tracking [PDF]
, 2016 In this paper we present a tracker, which is radically different from state-of-the-art trackers: we apply no model updating, no occlusion detection, no combination of trackers, no geometric matching, and still deliver state-of-the-art tracking ...
Gavves, Efstratios +2 more
core +2 more sources
Semi-supervised Learning Using Siamese Networks [PDF]
, 2019 added link of GitHub ...
Sahito, Attaullah +2 more
openaire +2 more sources
Few Shot Learning in Histopathological Images:Reducing the Need of Labeled Data on Biological Datasets [PDF]
, 2019 Although deep learning pathology diagnostic algorithms are proving comparable results with human experts in a wide variety of tasks, they still require a huge amount of well annotated data for training.
Belar, Oihana +7 more
core +1 more source
Re-Identification With Consistent Attentive Siamese Networks [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 10 pages, 8 figures, 3 tables, to appear in CVPR ...
Zheng, Meng +3 more
openaire +2 more sources
Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network
IEEE Access, 2022 Dairy cow face recognition using Neural Networks has several hurdles. For example, there are only a few instances of each individual. The positions and angles of the individuals in the image fluctuate considerably, the differences between individuals are
Feng Xu, Jing Gao, Xin Pan
doaj +1 more source
KD-Fixmatch: Knowledge Distillation Siamese Neural Networks
2023 IEEE International Conference on Image Processing (ICIP), 2023 Semi-supervised learning (SSL) has become a crucial approach in deep learning as a way to address the challenge of limited labeled data. The success of deep neural networks heavily relies on the availability of large-scale high-quality labeled data. However, the process of data labeling is time-consuming and unscalable, leading to shortages in labeled ...
Wang, Chien-Chih +4 more
openaire +2 more sources