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Siamese Neural Networks: An Overview
2020Similarity 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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Binary hashing using siamese neural networks
2017 IEEE International Conference on Image Processing (ICIP), 2017With 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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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), 2019Recently, 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 +3 more
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Characters Verification via Siamese Convolutional Neural Network
2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2018In the printing and carving industries, it is necessary to check whether printed outputs or carved wares are missing or etched through comparing the drawings. Traditional approaches and identification methods can’t be used for this application where the number of character categories are not determined, and where the character may be unique designed by
Shengke Wang +4 more
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Knowledge Transfer for Entity Resolution with Siamese Neural Networks
Journal of Data and Information Quality, 2021The integration of multiple data sources is a common problem in a large variety of applications. Traditionally, handcrafted similarity measures are used to discover, merge, and integrate multiple representations of the same entity—duplicates—into a large homogeneous collection of data.
Loster, Michael (Dr.) +2 more
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FACE RECOGNITION WITH SIAMESE NEURAL NETWORKS
Journal of Problems in Computer Science and Information TechnologiesThe development of face recognition technologies has become increasingly critical due to the growing need for effective identification methods. Traditional techniques often struggle with variations in illumination, pose, and facial expressions, limiting their applicability in real-world scenarios.
Bolatzhan Kumalakov +1 more
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Deep heterogeneous network embedding based on Siamese Neural Networks
Neurocomputing, 2020Abstract 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 +4 more
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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, 2020Data 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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Signature Recognition using Siamese Neural Networks
2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC), 2021Voruganti Ajay Krishna +2 more
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Siamese Neural Networks for Kannada Handwritten Dataset
2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT), 2022S Tejas, Kusumika Krori Dutta
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