Results 21 to 30 of about 5,338 (265)

Distilled Siamese Networks for Visual Tracking

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
In recent years, Siamese network based trackers have significantly advanced the state-of-the-art in real-time tracking. Despite their success, Siamese trackers tend to suffer from high memory costs, which restrict their applicability to mobile devices with tight memory budgets. To address this issue, we propose a distilled Siamese tracking framework to
Jianbing Shen, Yuanpei Liu, Xingping Dong, Xiankai Lu, Fahad Shahbaz Khan, Steven Hoi   +5 more
openaire   +4 more sources

Siamese network features for image matching [PDF]

2016 23rd International Conference on Pattern Recognition (ICPR), 2016
Finding matching images across large datasets plays a key role in many computer vision applications such as structure-from-motion (SfM), multi-view 3D reconstruction, image retrieval, and image-based localisation. In this paper, we propose finding matching and non-matching pairs of images by representing them with neural network based feature vectors ...
Kannala, Juho, Rahtu, Esa, Melekhov, Iaroslav   +3 more
openaire   +4 more sources

SpeakerNet for Cross-lingual Text-Independent Speaker Verification

Archives of Acoustics, 2020
Biometrics provide an alternative to passwords and pins for authentication. The emergence of machine learning algorithms provides an easy and economical solution to authentication problems.
Hafsa HABIB, Huma TAUSEEF, Muhammad Abuzar FAHIEM, Saima FARHAN, Ghousia USMAN   +4 more
doaj   +1 more source

Inverted Residual Siamese Visual Tracking With Feature Crossing Network

IEEE Access, 2021
Siamese networks based visual tracking has recently drawn great attention due to their superior representation and tracking accuracy. However, the backbone networks and prediction networks still cannot fully take advantage of features from modern deep ...
Feng Zhang, Xiaoyan Qian, Lei Han, Yi Shen   +3 more
doaj   +1 more source

A strong feature representation for siamese network tracker [PDF]

Multimedia Tools and Applications, 2020
Object tracking has important application in assistive technologies for personalized monitoring. Recent trackers choosing AlexNet as their backbone to extract features have gained great success. However, AlexNet is too shallow to form a strong feature representation, the tracker based on the Siamese network have an accuracy gap compared with state-of ...
Zhipeng Zhou, Rui Zhang, Dong Yin
openaire   +2 more sources

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, Jin Sun, Yong Zhang, Longquan Jiang 0002, Zhiliang Weng, Or Biran   +5 more
openaire   +2 more sources

Siamese meta-learning network for social disputes based on multi-head attention [PDF]

PeerJ Computer Science
Few-shot learning has been widely used in scenarios where labeled data is scarce, where meta-learning based few-shot classification is widely used, such as the Siamese network.
Jing Wang, Rui Zhang, Huijian Han, Yuxiang Liu, Zhaoxing Peng   +4 more
doaj   +2 more sources

Research on few-shot power detection of siamese network based on improved RPN

Journal of Hebei University of Science and Technology, 2023
In order to solve the problems of difficulty, low efficiency, and insufficient data to support large-scale training in existing power system detection methods, a few-shot detection method based on siamese network was proposed.
Jun FENG, Sichen PAN, Shuai ZHAO, Liangying PENG, Xiongfei FAN   +4 more
doaj   +1 more source

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, Christos Tachtatzis, Robert C. Atkinson, Ethan Bayne, Xavier J. A. Bellekens   +4 more
openaire   +4 more sources

Multiple Object Tracking via Feature Pyramid Siamese Networks

IEEE Access, 2019
When multiple object tracking (MOT) based on the tracking-by-detection paradigm is implemented, the similarity metric between the current detections and existing tracks plays an essential role. Most of the MOT schemes based on a deep neural network learn
Sangyun Lee, Euntai Kim
doaj   +1 more source