Results 131 to 140 of about 21,191 (172)

Attributed Network Embedding via a Siamese Neural Network

2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2019
Recently, network embedding has attracted a surge of attention due to its ability to automatically extract features from graph-structured data. Though network embedding method has been intensively studied, most of the existing approaches pay attention to either structures or attributes.
Jiong Wang, Neng Gao, Jia Peng, Jingjie Mo   +3 more
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Binary hashing using siamese neural networks

2017 IEEE International Conference on Image Processing (ICIP), 2017
With the growth in multimedia data, it is the need of the hour to have methods for efficient storage and quick retrieval. In this work, we propose an approach for learning binary codes for fast image retrieval. We use a siamese architecture with two parallel feed forward branches but with a shared weight for the generation of binary codes. The training
Abin Jose, Shen Yan, Iris Heisterklaus
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Deep heterogeneous network embedding based on Siamese Neural Networks

Neurocomputing, 2020
Abstract Heterogeneous network embedding aims at mapping a heterogeneous network into a low-dimensional latent space. There exist diverse relations among different types of objects in heterogeneous networks. However, most existing heterogeneous network embedding methods focus on exploring network structures instead of relations among different ...
Chen Zhang 0015, Zhouhua Tang, Bin Yu 0011, Yu Xie, Ke Pan   +4 more
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Siamese Neural Networks: An Overview

2020
Similarity has always been a key aspect in computer science and statistics. Any time two element vectors are compared, many different similarity approaches can be used, depending on the final goal of the comparison (Euclidean distance, Pearson correlation coefficient, Spearman's rank correlation coefficient, and others). But if the comparison has to be
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Siamese Neural Network for Unstructured Data Linkage

Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services, 2020
Data integration is one of the key problems in the era of Big Data analytics. The key challenge of data integration is the identification of records representing the same entities (e.g. person). This task is referred to as Record Linkage. It is uncommon for different data sources to share a unique identifier hence the records must be matched by ...
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Siamese Convolutional Neural Network for ASL Alphabet Recognition

Computación y Sistemas, 2020
American sign language is an important communication way to convey information among the deaf community in North America and is primarily used by people who have hearing or speech impairments. The deaf community faces a struggle in schools and other institutions because they usually consist primarily of hearing people.
Atoany Nazareth Fierro-Radilla, Karina R. Perez-Daniel   +1 more
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SiaSL: A Siamese Neural Network for Service Level Prediction

2021 IEEE International Conference on Web Services (ICWS), 2021
Service level is an important metric to measure the reasonability of service systems. However, traditional mathematical service level prediction models have strict restrictions and suffer from accuracy degradation in complex real scenarios. In this paper, we propose to use a Siamese neural network to solve the service level prediction problem.
Chenyu Hou, Bin Cao 0004
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Face Recognition via Convolutional Neural Networks and Siamese Neural Networks

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS), 2019
Deep convolutional neural networks is playing very important role to solve computer vision task in these decades. In this research has shown implementation state of art face recognition methods and compared them. Advantages and disadvantages of Convolutional and Siamese neural networks is explored for the face recognition task.
Wanxin Cui, Wei Zhan, Jingjing Yu, Chenfan Sun, Yangyang Zhang   +4 more
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Target Tracking Based on Siamese Convolution Neural Networks

2020 International Conference on Computer, Information and Telecommunication Systems (CITS), 2020
Target tracking is an important research content in the field of computer vision. There is a problem that speed and precision of tracking can’t be balanced. Aim at this problem, this paper proposes a Siamese-SE deep neural network, which is an improvement in the structure of the Siamese-FC Network that add the SE-Network to the network to improve the ...
Haibo Pang, Qi Xuan 0002, Meiqin Xie, Chengming Liu, Zhanbo Li   +4 more
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Matching ostraca fragments using a siamese neural network

Pattern Recognition Letters, 2020
Abstract As part of sociological studies, artifacts such as pottery ostraca from Upper Egypt are studied by egyptologists. These pottery pieces are covered with textual inscriptions many of which concern accounting and other economic and administrative matters.
Cecilia Ostertag, Marie Beurton-Aimar
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