A Comparative Study of Three Measurement Methods of Chinese Character Recognition for L2 Chinese Learners [PDF]
Frontiers in Psychology, 2022 Measuring Chinese character recognition ability is essential in research on character learning among learners of Chinese as a second language (CSL).
Haiwei Zhang +3 more
doaj +2 more sources
MA-CharNet: Multi-angle fusion character recognition network [PDF]
PLoS ONE, 2022 Irregular text recognition of natural scene is a challenging task due to large span of character angles and morphological diversity of a word. Recent work first rectifies curved word region, and then employ sequence algorithm to complete the recognition ...
Qingyu Wang +3 more
doaj +3 more sources
Air-Writing Character Recognition with Ultrasonic Transceivers [PDF]
Sensors, 2021 The interfaces between users and systems are evolving into a more natural communication, including user gestures as part of the interaction, where air-writing is an emerging application for this purpose.
Borja Saez-Mingorance +5 more
doaj +2 more sources
A Modified Back Propagation Algorithm for Assyrian Optical Character Recognition Based on Moments [PDF]
Engineering and Technology Journal, 2016 Character recognition has been very popular and interested area for researches, and it continues to be a challenging and impressive research topic due to its diverse applicable environment.
Luma Fayeq Jalil, Modhar Mohsen Mohammed
doaj +2 more sources
Linguistic-visual based multimodal Yi character recognition [PDF]
Scientific ReportsThe recognition of Yi characters is challenged by considerable variability in their morphological structures and complex semantic relationships, leading to decreased recognition accuracy.
Haipeng Sun +5 more
doaj +2 more sources
Convolutional Neural Networks for Handwritten Javanese Character Recognition
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2018 Convolutional neural network (CNN) is state-of-the-art method in object recognition task. Specialized for spatial input data type, CNN has special convolutional and pooling layers which enable hierarchical feature learning from the input space.
Chandra Kusuma Dewa +2 more
doaj +2 more sources
Handwritten Bangla Character Recognition Using the State-of-the-Art Deep Convolutional Neural Networks [PDF]
Computational Intelligence and Neuroscience, 2018 In spite of advances in object recognition technology, handwritten Bangla character recognition (HBCR) remains largely unsolved due to the presence of many ambiguous handwritten characters and excessively cursive Bangla handwritings.
Md Zahangir Alom +4 more
openalex +2 more sources
Full depth CNN classifier for handwritten and license plate characters recognition [PDF]
PeerJ Computer Science, 2021 Character recognition is an important research field of interest for many applications. In recent years, deep learning has made breakthroughs in image classification, especially for character recognition.
Mohammed Salemdeeb, Sarp Ertürk
doaj +2 more sources
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models [PDF]
AAAI Conference on Artificial Intelligence, 2021 Text recognition is a long-standing research problem for document digitalization. Existing approaches are usually built based on CNN for image understanding and RNN for char-level text generation.
Minghao Li +7 more
semanticscholar +1 more source
DTrOCR: Decoder-only Transformer for Optical Character Recognition [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2023 Typical text recognition methods rely on an encoder-decoder structure, in which the encoder extracts features from an image, and the decoder produces recognized text from these features.
Masato Fujitake
semanticscholar +1 more source