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MA-CRNN: a multi-scale attention CRNN for Chinese text line recognition in natural scenes
International Journal on Document Analysis and Recognition (IJDAR), 2019The recognition methods for Chinese text lines, as an important component of optical character recognition, have been widely applied in many specific tasks. However, there are still some potential challenges: (1) lack of open Chinese text recognition dataset; (2) challenges caused by the characteristics of Chinese characters, e.g., diverse types ...
Guofeng Tong +5 more
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CRNN: Integrating classification rules into neural network
The 2013 International Joint Conference on Neural Networks (IJCNN), 2013Association classification has been an important type of the rule-based classification. A variety of approaches have been proposed to build a classifier based on classification rules. In the prediction stage of the extant approaches, most of the existing association classifiers use the ensemble quality measurement of each rule in a subset of rules to ...
Wei Li +4 more
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CRNN-Refined Spatiotemporal Transformer for Dynamic MRI reconstruction
Computers in Biology and MedicineMagnetic Resonance Imaging (MRI) plays a pivotal role in modern clinical practice, providing detailed anatomical visualization with exceptional spatial resolution and soft tissue contrast. Dynamic MRI, aiming to capture both spatial and temporal characteristics, faces challenges related to prolonged acquisition times and susceptibility to motion ...
Bin Wang +4 more
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A CRNN module for hand pose estimation
Neurocomputing, 2019Abstract Hand pose estimation plays an important role in human–computer interaction. The traditional way is to deal with a video stream frame by frame. However, since the gesture in the video is changing continuously, the adjacent frames must be highly related to each other.
Zhongxu Hu +5 more
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Research on Scene Text Recognition Algorithm Basedon Improved CRNN
Proceedings of the 2020 4th International Conference on Digital Signal Processing, 2020Image-based sequence recognition has always been a longstanding research topic in computer vision. Scene text recognition is one of the most important and challenging tasks in image-based sequence recognition. End-to-end scene text recognition based on deep learning now mainly transforms text recognition into sequence recognition problems.
Yilin Chen, Juan Yang
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Grouping of multiple models from one ECG Using CRNN
2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC), 2021The customized depiction of heart rhythms using transient single-lead ECG recordings is a difficult task, which has recently received a lot of research attention. This research study presents the novel techniques, which attempts to possibly build ECG signals such as Atrial Fibrillation (Afib), Normal, Other Rhythms, or extremely noisy.
Jyothi Jarugula +5 more
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Cultural Symbol Recognition Algorithm Based on CTPN + CRNN
2021This paper proposes a cultural symbol recognition algorithm based on CTPN + CRNN. The algorithm uses the improved VGG16 + BLSTM network to extract the depth features and sequence features of the text image, and uses the Anchor to locate the text position. Finally, the task of cultural symbol recognition is carried out through the CNN + BLSTM + CTC deep
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Handwritten Text Recognition Using CRNN
2022 8th International Conference on Contemporary Information Technology and Mathematics (ICCITM), 2022Ahmed A. Idris, Dujan B. Taha
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Speech Emotion Recognition Model Based on CRNN-CTC
2020CRNN (Convolutional Recurrent Neural Network) deep learning model is currently a typical speech emotion recognition technology. When this model is applied, no matter how long the speech sequence is, it will only be converted into an emotional tag. However, the emotional information in speech samples is generally unevenly distributed between frames ...
Zijiang Zhu +4 more
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CRNN-Based Abstract Artistic Text Recognition
2023 IEEE Smart World Congress (SWC), 2023Zhuoyue Tan, Jing Zhou, Yang Liu
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