Results 31 to 40 of about 423 (132)

Tibetan Data Augmentation via GAN‐Based Handwritten Text Generation

CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 55-65, February 2026.
ABSTRACT Increased awareness of Tibetan cultural preservation, along with technological advancements, has led to significant efforts in academic research on Tibetan. However, the structural complexity of the Tibetan language and limited labeled handwriting data impede advancements in Optical Character Recognition (OCR) and other applications.
Dorje Tashi, Bingtian Chen, Tianying Sheng, Yongbin Yu, Xiangxiang Wang, Jin Zhang, Lobsang Yeshi, Rinchen Dongrub, Thupten Tsering, Nyima Tashi   +9 more
wiley   +1 more source

End to End Alignment Learning of Instructional Videos with Spatiotemporal Hybrid Encoding and Decoding Space Reduction

Applied Sciences, 2021
We solve the problem of how to densely align actions in videos at frame level, with only the order of occurring actions available, in order to save the time-consuming efforts to accurately annotate the temporal boundaries of each action. We propose three
Lin Wang, Xingfu Wang, Ammar Hawbani, Yan Xiong   +3 more
doaj   +1 more source

A deep neural network-based automatic mispronunciation detection in Bengali accented English speech

Discover Computing
Learning a second language, especially English, became necessary as globalisation started. One crucial component of language learning resources is computer-assisted pronunciation training, or CAPT.
Puja Bharati, Sabyasachi Chandra, Aniket Aitawade, Debolina Pramanik, Satya Prasad Gaddamedi, Shyamal Kumar Das Mandal   +5 more
doaj   +1 more source

Attention-based deep learning model for Arabic handwritten text recognition

Machine Graphics & Vision, 2022
This work proposes a segmentation-free approach to Arabic Handwritten Text Recognition (AHTR): an attention-based Convolutional Neural Network - Recurrent Neural Network - Connectionist Temporal Classification (CNN-RNN-CTC) deep learning architecture ...
Takwa Ben Aïcha Gader, Afef Kacem Echi
doaj   +1 more source

Hybrid Deep Learning Frameworks for License Plate Recognition in Complex Environments: A Comprehensive Survey and Research Outlook

IET Computer Vision, Volume 20, Issue 1, January/December 2026.
This survey systematically reviews state‐of‐the‐art license plate recognition methods, with a focus on hybrid CNN‐transformer frameworks and the joint optimisation of detection and recognition for real‐world deployment. It further analyses existing datasets, highlights persistent challenges, such as domain generalisation, and outlines pathways towards ...
SanXing Deng, Ewe Lay Sheng, Tiong Sieh Kiong, MengMeng Yang   +3 more
wiley   +1 more source

Uncertainty‐Aware Processing for OCR Using Dictionary Routing and Candidate Selection

Electronics Letters, Volume 62, Issue 1, January/December 2026.
This paper proposes an Uncertainty‐Aware Processing (UAP) framework that reduces the Character Error Rate (CER) without additional training or inference. The method calculates two metrics using the results of Connectionist Temporal classification (CTC). These two metrics are used to estimate a character‐level uncertainty.
Gi Hoon Kim, JiU Bak, Hyunguk Choi
wiley   +1 more source

An Input-synchronous Blockwise Decoding Algorithm for CTC-AED Speech Recognition

Информатика и автоматизация
Automatic speech recognition (ASR) systems for real-life scenarios are required to process audio streams of arbitrary length with stable accuracy under limited computational resources.
Iurii Lezhenin, Natalia Bogach
doaj   +1 more source

Advances in Detecting RNA Modifications Using Direct RNA Nanopore Sequencing

Advanced Genetics, Volume 6, Issue 4, December 2025.
This review examines recent advances in Oxford Nanopore Technologies direct RNA sequencing, highlighting its expanding capacity to detect RNA modifications beyond m6A. It discusses computational frameworks and basecalling innovations that enable single‐nucleotide and single‐molecule resolution, explores co‐occurring modifications and their regulatory ...
Yaran Liu, Yang Li, Qiang Sun
wiley   +1 more source

Bidirectional Representations for Low-Resource Spoken Language Understanding

Applied Sciences, 2023
Speech representation models lack the ability to efficiently store semantic information and require fine tuning to deliver decent performance. In this research, we introduce a transformer encoder–decoder framework with a multiobjective training strategy,
Quentin Meeus, Marie-Francine Moens, Hugo Van hamme   +2 more
doaj   +1 more source

Freight rail activity inventory system using a vision‐based deep learning framework

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 27, Page 4692-4717, 14 November 2025.
Abstract Rail freight serves as a reliable cost‐effective and fuel‐efficient mode for long‐distance ground freight transportation. Existing rail data sources rely heavily on aggregate reports that lead to significant spatiotemporal data gaps for infrastructure planning and regulatory evaluation.
Guoliang Feng, Yiqiao Li, Andre Y. C. Tok, Stephen G. Ritchie   +3 more
wiley   +1 more source