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- ArticleJuly 2024
Expiration Date Recognition System Using Spatial Transformer Network for Visually Impaired
Computers Helping People with Special NeedsPages 517–524https://doi.org/10.1007/978-3-031-62846-7_61AbstractIn this paper, we propose a system for recognizing an expiration date of a beverge package. A visually impaired user takes a photo of the product. Then, the system automatically recognizes the expiration date of the product and tells it to the ...
- ArticleDecember 2023
Unsupervised Fingerprint Dense Registration
AbstractFingerprint registration is still a challenging task due to the large variation of fingerprint quality. Meanwhile, existing supervised fingerprint registration methods need sufficient amount of labeled fingerprint pairs which are difficult to ...
- research-articleApril 2021
Research Approach of Hand Gesture Recognition based on Improved YOLOV3 network and Bayes classifier
ICVIP '20: Proceedings of the 2020 4th International Conference on Video and Image ProcessingPages 140–146https://doi.org/10.1145/3447450.3447473The study of gesture recognition is closely related to the harmonious development of human-computer interaction, which has important research significance. Aiming at the problems of long detection time and low recognition efficiency of traditional ...
- ArticleSeptember 2018
Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
- Chen Qin,
- Wenjia Bai,
- Jo Schlemper,
- Steffen E. Petersen,
- Stefan K. Piechnik,
- Stefan Neubauer,
- Daniel Rueckert
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018Pages 472–480https://doi.org/10.1007/978-3-030-00934-2_53AbstractCardiac motion estimation and segmentation play important roles in quantitatively assessing cardiac function and diagnosing cardiovascular diseases. In this paper, we propose a novel deep learning method for joint estimation of motion and ...
- ArticleSeptember 2018
Pairwise Confusion for Fine-Grained Visual Classification
AbstractFine-Grained Visual Classification (FGVC) datasets contain small sample sizes, along with significant intra-class variation and inter-class similarity. While prior work has addressed intra-class variation using localization and segmentation ...