Results 171 to 180 of about 8,202,971 (220)

MorphText: Deep Morphology Regularized Accurate Arbitrary-Shape Scene Text Detection

IEEE transactions on multimedia, 2023
Bottom-up text detection methods play an important role in arbitrary-shape scene text detection but there are two restrictions preventing them from achieving their great potential, i.e., 1) the accumulation of false text segment detections, which affects
Chengpei Xu, W. Jia, Ruomei Wang, Xiaonan Luo, Xiangjian He   +4 more
semanticscholar   +1 more source

Object and Text Detection

KEC Journal of Science and Engineering, 2023
The main aim of our project is to develop a portable raspberry pi implemented gadget for object detection with relative motion and distance. This technology is basically used for conversion of sequence of real time objects into series of text which can be further stored into database and can be utilized to assist visually impaired people and in various
Pooja Singh, Richa Pokhrel, Asmita Jha, Pragya Jha, Saroj Shakya   +4 more
openaire   +1 more source

Reinforcement Shrink-Mask for Text Detection

IEEE transactions on multimedia, 2023
Existing real-time text detectors reconstruct text contours by shrink-masks only. Though they simplify the framework and can make the model run fast, the strong dependence on shrink-masks leads to unreliable detection results (e.g., miss detection and ...
Chuan Yang, Mulin Chen, Yuan Yuan, Qi Wang   +3 more
semanticscholar   +1 more source

Con-Text: Text Detection for Fine-Grained Object Classification

IEEE Transactions on Image Processing, 2017
This paper focuses on fine-grained object classification using recognized scene text in natural images. While the state-of-the-art relies on visual cues only, this paper is the first work which proposes to combine textual and visual cues. Another novelty is the textual cue extraction. Unlike the state-of-the-art text detection methods, we focus more on
Sezer Karaoglu, Ran Tao, Jan C. van Gemert, Theo Gevers   +3 more
openaire   +3 more sources

M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection

Annual Meeting of the Association for Computational Linguistics
The advent of Large Language Models (LLMs) has brought an unprecedented surge in machine-generated text (MGT) across diverse channels. This raises legitimate concerns about its potential misuse and societal implications.
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, A. Tsvigun, Osama Mohanned Afzal, Tarek Mahmoud, Giovanni Puccetti, Thomas Arnold, Alham Fikri Aji, Nizar Habash, Iryna Gurevych, Preslav Nakov   +13 more
semanticscholar   +1 more source

Progressive Contour Regression for Arbitrary-Shape Scene Text Detection

Computer Vision and Pattern Recognition, 2021
State-of-the-art scene text detection methods usually model the text instance with local pixels or components from the bottom-up perspective and, therefore, are sensitive to noises and dependent on the complicated heuristic post-processing especially for
Pengwen Dai, Sanyi Zhang, Hua Zhang, Xiaochun Cao   +3 more
semanticscholar   +1 more source

SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection

International Workshop on Semantic Evaluation
We present the results and the main findings of SemEval-2024 Task 8: Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection. The task featured three subtasks. Subtask A is a binary classification task determining whether a text is
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, A. Tsvigun, Osama Mohammed Afzal, Tarek Mahmoud, Giovanni Puccetti, Thomas Arnold, Chenxi Whitehouse, Alham Fikri Aji, Nizar Habash, Iryna Gurevych, Preslav Nakov   +14 more
semanticscholar   +1 more source

AI-Generated Text Detection and Classification Based on BERT Deep Learning Algorithm

Theoretical and Natural Science
With the rapid development and wide application of deep learning technology, AI-generated text detection plays an increasingly important role in various fields.
Hao Wang, Jianwei Li, Zhengyu Li
semanticscholar   +1 more source

Arbitrary Shape Text Detection via Segmentation With Probability Maps

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Arbitrary shape text detection is a challenging task due to the significantly varied sizes and aspect ratios, arbitrary orientations or shapes, inaccurate annotations, etc.
Shi-Xue Zhang, Xiaobin Zhu, Lei Chen, Jie-Bo Hou, Xu-Cheng Yin   +4 more
semanticscholar   +1 more source

Scene Text Detection Based on Text Stroke Components

International Journal of Neural Systems
The detection of scene text holds significant importance across a variety of application scenarios. However, previous methods were insufficient for detecting and recognizing text instances, such as variations in text size, chaotic background and diverse text orientations.
Xinyue Hou, Pengsen Cheng, Hongyu Gao, Xin Li, Jiayong Liu   +4 more
openaire   +2 more sources