Results 81 to 90 of about 8,202,971 (220)
A Post-Processing Method for Text Detection Based on Geometric Features
IEEE Access, 2021 Deep learning text detection is generally divided into two steps: prediction candidate box of depth model and post-processing, and post-processing usually uses NMS or prediction box to merge and connect.
Xiaogang Qiu +4 more
doaj +1 more source
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, 2008 Text reuse occurs in many different types of documents and for many different reasons. One form of reuse, duplicate or near-duplicate documents, has been a focus of researchers because of its importance in Web search. Local text reuse occurs when sentences, facts or passages, rather than whole documents, are reused and modified.
Jangwon Seo, W. Bruce Croft
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Letter detection in very familiar texts [PDF]
Memory & Cognition, 2001 In the present study, we investigated whether patterns of letter detection for function and content words in texts are affected by the familiarity of the material being read. In Experiment 1, subjects searched for target letters in sentences that had been rehearsed prior to performing the letter detection on them as well as on unfamiliar sentences.
S N, Greenberg, J, Tai
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ContourNet: Taking a Further Step Toward Accurate Arbitrary-Shaped Scene Text Detection [PDF]
Computer Vision and Pattern Recognition, 2020 Scene text detection has witnessed rapid development in recent years. However, there still exists two main challenges: 1) many methods suffer from false positives in their text representations; 2) the large scale variance of scene texts makes it hard for
Yuxin Wang +5 more
semanticscholar +1 more source
MTRNet: A Generic Scene Text Eraser
, 2019 Text removal algorithms have been proposed for uni-lingual scripts with regular shapes and layouts. However, to the best of our knowledge, a generic text removal method which is able to remove all or user-specified text regions regardless of font, script,
Denman, Simon +5 more
core +1 more source
Enhanced Characterness for Text Detection in the Wild
, 2017 Text spotting is an interesting research problem as text may appear at any random place and may occur in various forms. Moreover, ability to detect text opens the horizons for improving many advanced computer vision problems.
Agrawal, Aarushi +3 more
core +1 more source
Text Detection on Images using Region-based Convolutional Neural Network
UHD Journal of Science and Technology, 2020 In this paper, a new text detection algorithm that accurately locates picture text with complex backgrounds in natural images is applied. The approach is based primarily on the region-based convolutional neural network anchor system, which takes into ...
Hamsa D. Majeed
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Detecting Oriented Text in Natural Images by Linking Segments
, 2017 Most state-of-the-art text detection methods are specific to horizontal Latin text and are not fast enough for real-time applications. We introduce Segment Linking (SegLink), an oriented text detection method.
Bai, Xiang +2 more
core +1 more source
Text-driven online action detection
Integrated Computer-Aided EngineeringDetecting actions as they occur is essential for applications like video surveillance, autonomous driving, and human-robot interaction. Known as online action detection, this task requires classifying actions in streaming videos, handling background noise, and coping with incomplete actions.
Benavent-Lledó, Manuel +3 more
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Abusive Text Detection Using Neural Networks [PDF]
CEUR Workshop Proceedings, 2017 Neural network models have become increasingly popular for text classification in recent years. In particular, the emergence of word embeddings within deep learning architectures has recently attracted a high level of attention amongst researchers. In this paper, we focus on how neural network models have been applied in text classification.
Chen, Hao +2 more
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