Results 71 to 80 of about 76,886 (181)

LSE-FS-UVigo Dataset and Keypoint-Based Fingerspelling Recognition

IEEE Access
Continuous fingerspelling recognition remains a challenging task due to rapid hand and finger movements, coarticulation, and the limited availability of annotated data across sign languages. We introduce LSE-FS-UVigo, the first open dataset of continuous
Jose Luis Ruanova-Lea, Jose Luis Alba-Castro, Laura Docio-Fernandez   +2 more
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

Probabilistic asr feature extraction applying context-sensitive connectionist temporal classification networks [PDF]

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
This paper proposes a novel automatic speech recognition (ASR) front-end that unites the principles of bidirectional Long Short-Term Memory (BLSTM), Connectionist Temporal Classification (CTC), and Bottleneck (BN) feature generation. BLSTM networks are known to produce better probabilistic ASR features than conventional multilayer perceptrons since ...
Martin Wöllmer, Björn W. Schuller, Gerhard Rigoll   +2 more
openaire   +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

Focal CTC Loss for Chinese Optical Character Recognition on Unbalanced Datasets

Complexity, 2019
In this paper, we propose a novel deep model for unbalanced distribution Character Recognition by employing focal loss based connectionist temporal classification (CTC) function.
Xinjie Feng, Hongxun Yao, Shengping Zhang   +2 more
doaj   +1 more source

The Agent Preference in Ontogeny: Predictability of Agent and Patient Roles in Child‐Directed Utterances Across Languages

Cognitive Science, Volume 50, Issue 1, January 2026.
Abstract Language comprehension unfolds incrementally, requiring listeners to continually predict and revise interpretations. Comprehenders across very diverse languages show a consistent preference for agents, anticipating the agent (“the doer” of an action) more strongly than the patient (“the undergoer”). An unresolved question is how the preference
Eva Huber, Aylin C. Küntay, Balthasar Bickel, Sabine Stoll   +3 more
wiley   +1 more source

Shared Minds: The Cognitive Parallels Between Humans and Artificial Intelligence

Human Behavior and Emerging Technologies, Volume 2026, Issue 1, 2026.
This narrative review integrates evidence from cognitive science and AI research to challenge commonly accepted dichotomies between human and artificial cognition, such as the assumed divide between genuine human understanding and mere machine pattern matching. Instead, we propose a view that recognises similarities in their cognitive architectures and
Sébastien Tremblay, Alexandre Marois, Marzieh Zare, Daniel Lafond, Tze Wei Liew   +4 more
wiley   +1 more source

In Situ Graph Reasoning and Knowledge Expansion Using Graph‐PRefLexOR

Advanced Intelligent Discovery, Volume 1, Issue 3, December 2025.
Graph‐PRefLexOR is a novel framework that enhances language models with in situ graph reasoning, symbolic abstraction, and recursive refinement. By integrating graph‐based representations into generative tasks, the approach enables interpretable, multistep reasoning.
Markus J. Buehler
wiley   +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

Text-Independent Phone-to-Audio Alignment Leveraging SSL (TIPAA-SSL) Pre-Trained Model Latent Representation and Knowledge Transfer

Acoustics
In this paper, we present a novel approach for text-independent phone-to-audio alignment based on phoneme recognition, representation learning and knowledge transfer.
Noé Tits, Prernna Bhatnagar, Thierry Dutoit   +2 more
doaj   +1 more source