Results 31 to 40 of about 26,674 (270)

Exploring Recurrent Neural Networks for On-Line Handwritten Signature Biometrics

open access: yesIEEE Access, 2018
Systems based on deep neural networks have made a breakthrough in many different pattern recognition tasks. However, the use of these systems with traditional architectures seems not to work properly when the amount of training data is scarce.
Ruben Tolosana   +3 more
doaj   +1 more source

Enhancing Text Similarity Measurement with Hybrid Siamese Neural Networks and Lexical Features [PDF]

open access: yesAdvances in Engineering and Intelligence Systems
Accurately measuring text similarity holds significant importance in various text-centric applications, including text clustering, information retrieval, and question/answer systems.
Bei Zhou
doaj   +1 more source

SNS-CF: Siamese Network with Spatially Semantic Correlation Features for Object Tracking

open access: yesSensors, 2020
Recent advances in object tracking based on deep Siamese networks shifted the attention away from correlation filters. However, the Siamese network alone does not have as high accuracy as state-of-the-art correlation filter-based trackers, whereas ...
Thierry Ntwari   +3 more
doaj   +1 more source

A Siamese Network Based U-Net for Change Detection in High Resolution Remote Sensing Images

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Remote sensing image change detection (RSICD) is a technique that explores the change of surface coverage in a certain time series by studying the difference between multiple remote sensing images (RSIs) collected over the same area.
Tao Chen   +5 more
doaj   +1 more source

Target tracking method of Siamese networks based on the broad learning system

open access: yesCAAI Transactions on Intelligence Technology, 2023
Target tracking has a wide range of applications in intelligent transportation, real‐time monitoring, human‐computer interaction and other aspects. However, in the tracking process, the target is prone to deformation, occlusion, loss, scale variation ...
Dan Zhang   +4 more
doaj   +1 more source

Rotation Equivariant Siamese Networks for Tracking [PDF]

open access: yes2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Rotation is among the long prevailing, yet still unresolved, hard challenges encountered in visual object tracking. The existing deep learning-based tracking algorithms use regular CNNs that are inherently translation equivariant, but not designed to tackle rotations.
Gupta, D.K., Arya, D., Gavves, E.
openaire   +4 more sources

Masked Siamese Networks for Label-Efficient Learning

open access: yes, 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.
Assran, Mahmoud   +8 more
openaire   +2 more sources

SiamFT: An RGB-Infrared Fusion Tracking Method via Fully Convolutional Siamese Networks

open access: yesIEEE Access, 2019
Object tracking based on visible images may fail when the visible images are unreliable, for example when the illumination condition is poor. Infrared images reveal thermal radiation of objects and are insensitive to these factors.
Xingchen Zhang   +5 more
doaj   +1 more source

Siamese Dense Neural Network for Software Defect Prediction With Small Data

open access: yesIEEE Access, 2019
Software defect prediction (SDP) exerts a major role in software development, concerning reducing software costs and ensuring software quality. However, developing an accurate SDP model is still a severe and challenging task with the lack of training ...
Linchang Zhao   +4 more
doaj   +1 more source

SCCNN: A Diagnosis Method for Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Siamese Cross Contrast Neural Network

open access: yesIEEE Access, 2020
This paper proposes a novel siamese cross contrast neural network (SCCNN) to classify the hepatocellular carcinoma (HCC) and the intrahepatic cholangiocarcinoma (ICC) on computed tomography (CT) images.
Qiyuan Wang   +8 more
doaj   +1 more source

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