Results 31 to 40 of about 4,140 (257)
Developing a Siamese Network for Intrusion Detection Systems [PDF]
Proceedings of the 1st Workshop on Machine Learning and Systems, 2021 Machine Learning (ML) for developing Intrusion Detection Systems (IDS) is a fast-evolving research area that has many unsolved domain challenges. Current IDS models face two challenges that limit their performance and robustness. Firstly, they require large datasets to train and their performance is highly dependent on the dataset size.
Hanan Hindy +4 more
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A Siamese Network Based U-Net for Change Detection in High Resolution Remote Sensing Images
IEEE 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
Siamese Networks for Semantic Pattern Similarity [PDF]
2019 IEEE 13th International Conference on Semantic Computing (ICSC), 2019 Semantic Pattern Similarity is an interesting, though not often encountered NLP task where two sentences are compared not by their specific meaning, but by their more abstract semantic pattern (e.g., preposition or frame). We utilize Siamese Networks to model this task, and show its usefulness in determining SQL patterns for unseen questions in a ...
Yassine Benajiba +5 more
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Exploring Recurrent Neural Networks for On-Line Handwritten Signature Biometrics
IEEE 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
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Enhancing Text Similarity Measurement with Hybrid Siamese Neural Networks and Lexical Features [PDF]
Advances in Engineering and Intelligence SystemsAccurately measuring text similarity holds significant importance in various text-centric applications, including text clustering, information retrieval, and question/answer systems.
Bei Zhou
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SNS-CF: Siamese Network with Spatially Semantic Correlation Features for Object Tracking
Sensors, 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
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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
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Siamese Network for Fake Item Detection. [PDF]
, 2023 Currently, most multimedia users choose to purchase items through e-commerce. Nevertheless, one of the main concerns of online shopping is the possibility of obtaining counterfeit products. Therefore, it is crucial to monitor the product's authenticity, thus adopting an automatic mechanism to validate the similarity between the purchased item and the ...
Erica Coppolillo +5 more
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Siamese networks for generating adversarial examples
CoRR, 2018 Machine learning models are vulnerable to adversarial examples. An adversary modifies the input data such that humans still assign the same label, however, machine learning models misclassify it. Previous approaches in the literature demonstrated that adversarial examples can even be generated for the remotely hosted model.
Mandar Kulkarni, Aria Abubakar
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SiamFT: An RGB-Infrared Fusion Tracking Method via Fully Convolutional Siamese Networks
IEEE 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
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