Suchergebnisse - "Handwriting Recognition and Text Detection"

Overview of the Grand Challenge on Detecting Cheapfakes at ACM ICMR 2024

Autoren: Duc-Tien Dang-Nguyen Sohail Ahmed Khan Michael A. Riegler et al.

Quelle: Proceedings of the 2024 International Conference on Multimedia Retrieval. :1275-1281

Schlagwörter: FOS: Computer and information sciences, Technology, Science & Technology, 4. Education, out-of-context media, re-contextualized media, Handwriting Recognition and Text Detection, 16. Peace & justice, Computer science, 7. Clean energy, Computer Science, Artificial Intelligence, 3. Good health, Web Data Extraction and Crawling Techniques, Computer Science, Theory & Methods, Computer Science, Physical Sciences, Image Forgery Detection, news, cheapfakes detection, Computer Vision and Pattern Recognition, Digital Image Forgery Detection and Identification, misinformation, 10. No inequality, Information Systems

Dateibeschreibung: application/pdf

Zugangs-URL: https://lirias.kuleuven.be/handle/20.500.12942/749972
https://doi.org/10.1145/3652583.3657587
https://hdl.handle.net/11250/3197231

Data Augmentation for Offline Arabic Handwritten Text Recognition Using Moving Least Squares

Autoren: Mohamed Amine Chadli Rochdi Bachir Bouiadjra Abdelkader Fekir et al.

Quelle: RUIdeRA. Repositorio Institucional de la UCLM
Universidad de Castilla-La Mancha

Schlagwörter: Arabic script, Artificial intelligence, Synthetic data, Data augmentation, Recurrent neural network, Digital Image Processing and Artificial Neural Networks, Convolutional neural network, Speech recognition, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Automatic License Plate Recognition System, Engineering, Connectionist temporal classification, Scene Text Recognition, Artificial Intelligence, Text Localization, Media Technology, Off-line handwritten recognition, Text Detection, Arabic, Natural language processing, 4. Education, Linguistics, 15. Life on land, IFN/ENIT database, Computer science, FOS: Philosophy, ethics and religion, Philosophy, 13. Climate action, Character Segmentation, Computer Science, Physical Sciences, FOS: Languages and literature, Computer Vision and Pattern Recognition, Handwriting Recognition

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/10578/43617
https://www.iieta.org/journals/ria/paper/10.18280/ria.380101

License plate text recognition using deep learning, NLP, and image processing techniques

Autoren: Hanae Moussaoui Nabil El Akkad Mohamed Benslimane

Quelle: Statistics, Optimization & Information Computing. 12:685-696

Schlagwörter: FOS: Computer and information sciences, Artificial intelligence, License, Speech recognition, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Automatic License Plate Recognition System, Engineering, Scene Text Recognition, Image processing, Media Technology, Image (mathematics), Number Plate Detection, Text recognition, Text Detection, MIT License, Vehicle Identification, Natural language processing, Deep learning, 16. Peace & justice, Computer science, Operating system, Digital Rights Management Architectures and Technologies, Physical Sciences, Computer Science, Computer Vision and Pattern Recognition, Automatic License Plate Recognition, Information Systems

Deep Learning Algorithms for Arabic Optical Character Recognition: A Survey

Autoren: Mazin Mustafa Mahdi Ahmed Sleem Ibrahim Elhenawy

Quelle: Multicriteria Algorithms with Applications. 2:65-79

Schlagwörter: Artificial intelligence, Character (mathematics), Character recognition, Geometry, Speech recognition, Handwriting Recognition and Text Detection, Automatic License Plate Recognition System, Engineering, Deep Learning, Media Technology, FOS: Mathematics, Image (mathematics), 14. Life underwater, Arabic, Real-Time Recognition, Natural language processing, 4. Education, Linguistics, Computer science, FOS: Philosophy, ethics and religion, Algorithm, Philosophy, Character Segmentation, Computer Science, Physical Sciences, FOS: Languages and literature, Computer Vision and Pattern Recognition, OCR Engine, Optical character recognition, Mathematics, Handwriting Recognition

HACR-MDL: HANDWRITTEN ARABIC CHARACTER RECOGNITION MODEL USING DEEP LEARNING

Autoren: Mazen Nabil Elagamy Maria Khalil Eman Abdel Rahman Ismail

Quelle: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-1-W1-2023, Pp 123-128 (2023)

Schlagwörter: Artificial neural network, Technology, Artificial intelligence, Character (mathematics), Character recognition, Digital Image Processing and Artificial Neural Networks, Geometry, Convolutional neural network, Speech recognition, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Intelligent word recognition, Automatic License Plate Recognition System, Engineering, Scene Text Recognition, Artificial Intelligence, Media Technology, Image (mathematics), FOS: Mathematics, Applied optics. Photonics, Scope (computer science), Curse of dimensionality, Text Detection, Arabic, Natural language processing, Deep learning, Linguistics, Engineering (General). Civil engineering (General), Computer science, TA1501-1820, FOS: Philosophy, ethics and religion, Programming language, Philosophy, Character Segmentation, Computer Science, Physical Sciences, FOS: Languages and literature, Computer Vision and Pattern Recognition, TA1-2040, Intelligent character recognition, Mathematics, Handwriting Recognition

Dateibeschreibung: application/pdf

Zugangs-URL: https://isprs-annals.copernicus.org/articles/X-1-W1-2023/123/2023/
https://doaj.org/article/84b3ad2ea2a14350b4a02b0ce2b54453

VISUAL OBSERVATION OF WOMEN’S TRADITIONAL BAJU KURUNG PATTERN GRADING ARRANGEMENT LAYOUT ON EXISTING BATIK FABRIC TO REDUCE FABRIC WASTE IN MALAYSIA

Autoren: Mohamad Shukri Che Ya Nazlina Shaari Noranita Mansor

Quelle: Journal of Creative Industry and Sustainable Culture. 2:66-80

Schlagwörter: Composite material, Engineering drawing, Computational Mechanics, Handwriting Recognition and Text Detection, Clothing, 12. Responsible consumption, Motion Synthesis and Control Techniques, N Visual arts (General) For photography, Engineering, 5. Gender equality, Fabric structure, 11. Sustainability, Analysis of Three-Dimensional Shape Structures, Civil engineering, 10. No inequality, Geography, see TR, Grading (engineering), Computer science, Materials science, Archaeology, Control and Systems Engineering, Physical Sciences, Computer Science, Computer Vision and Pattern Recognition, Texture Mapping, FOS: Civil engineering

Dateibeschreibung: application/pdf

A joint study of deep learning-based methods for identity document image binarization and its influence on attribute recognition

Autoren: Rubén Sánchez-Rivero Pavel Bezmaternykh Alexander Gayer et al.

Quelle: Компьютерная оптика, Vol 47, Iss 4, Pp 627-636 (2023)

Schlagwörter: Relation (database), optical character recognition, Artificial intelligence, Information theory, Handwriting Recognition and Text Detection, Binarization, Pattern recognition (psychology), Document Reconstruction, Automated Reconstruction of Fragmented Objects, Workflow, Database, Artificial Intelligence, Field (mathematics), Image (mathematics), FOS: Mathematics, Information retrieval, identity document recognition, Q350-390, Data mining, Preprocessor, sort, Physics, Pure mathematics, deep learning, Image Matching, Deep learning, QC350-467, Statistical Machine Translation and Natural Language Processing, Acoustics, Optics. Light, Document Image Analysis, Computer science, Identity (music), document image binarization, Computer Science, Physical Sciences, u-net architecture, Computer Vision and Pattern Recognition, Mathematics, Handwriting Recognition

Zugangs-URL: https://doaj.org/article/e262613e5eed4eaaa87175094a8af74b

An Efficient Text Recognition System from Complex Color Image for Helping the Visually Impaired Persons

Autoren: Ahmed Ben Atitallah Mohamed Amin Ben Atitallah Yahia Said et al.

Quelle: Computer Systems Science and Engineering. 46:701-717

Schlagwörter: Artificial intelligence, Automated Currency Recognition and Authentication, 02 engineering and technology, Speech recognition, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Automatic License Plate Recognition System, Engineering, Context (archaeology), Scene Text Recognition, Text Localization, Media Technology, Image (mathematics), General Circulation Model, 0202 electrical engineering, electronic engineering, information engineering, Climate change, Biology, Text recognition, Text Detection, Ecology, Natural language processing, 4. Education, Paleontology, Document Image Analysis, Computer science, Character Segmentation, FOS: Biological sciences, Computer Science, Physical Sciences, Computer Vision and Pattern Recognition, GCM transcription factors, Optical character recognition

In-Air Signature Verification System Based on Beta-Elliptical Approach and Fuzzy Perceptual Detector

Autoren: AbdulAzeez R. Alobaidi Thameur Dhieb Tarek M. Hamdani et al.

Quelle: IEEE Access, Vol 11, Pp 134058-134073 (2023)

Schlagwörter: Artificial intelligence, Geometry, In-air signature verification, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Automated Reconstruction of Fragmented Objects, Automatic License Plate Recognition System, Identification (biology), beta-elliptical approach, Engineering, Media Technology, FOS: Mathematics, Dynamic time warping, fuzzy perceptual detector, Data mining, Biology, Signature Verification, Preprocessor, Signature (topology), Botany, Detector, Computer science, TK1-9971, Biometrics, dynamic time warping, Computer Science, Physical Sciences, Telecommunications, Feature extraction, Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, Mathematics, Handwriting Recognition

Zugangs-URL: https://doaj.org/article/67493513c6944069982d314e4791f2ca

Recognizing Ancient South Indian Language Using Opposition Based Grey Wolf Optimization

Autoren: Anjan Kumar G. Geetha

Quelle: Intelligent Automation & Soft Computing. 35:2619-2637

Schlagwörter: Artificial neural network, Artificial intelligence, Particle swarm optimization, FOS: Political science, 4. Education, Politics, FOS: Law, 02 engineering and technology, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Computer science, 7. Clean energy, Opposition (politics), Algorithm, Automatic License Plate Recognition System, Engineering, Computer Science, Physical Sciences, Shape Matching and Object Recognition, Media Technology, 0202 electrical engineering, electronic engineering, information engineering, Computer Vision and Pattern Recognition, Political science, Law, Handwriting Recognition

Robust Arabic and Pashto Text Detection in Camera-Captured Documents Using Deep Learning Techniques

Autoren: Nisar Khan Riaz Ahmad Khalil Ullah et al.

Quelle: IEEE Access, Vol 11, Pp 135788-135796 (2023)

Schlagwörter: Artificial intelligence, Economics, Document image analysis, Speech recognition, Handwriting Recognition and Text Detection, Pashto, Document Reconstruction, Reliability engineering, Automated Reconstruction of Fragmented Objects, Unavailability, Automatic License Plate Recognition System, Task (project management), Engineering, Context (archaeology), Scene Text Recognition, Media Technology, Image (mathematics), dataset, Biology, Arabic, Text Detection, text detection, Natural language processing, 4. Education, Paleontology, Image Matching, Deep learning, Document Image Analysis, Scripting language, Computer science, TK1-9971, Management, Operating system, Computer Science, Physical Sciences, Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, CNN, Optical character recognition

Zugangs-URL: https://doaj.org/article/1b80cd9021ba4b5d81c7674a7373cc1d

Enhancing Handwritten Alphabet Prediction with Real-time IoT Sensor Integration in Machine Learning for Image

Autoren: R.K. Gautam Anurag Sinha Hassan Raza Mahmood et al.

Quelle: Journal of Smart Internet of Things. 2022:53-64

Schlagwörter: Artificial intelligence, Internet of Things, Handwriting Recognition and Text Detection, Pattern recognition (psychology), 7. Clean energy, Automated Reconstruction of Fragmented Objects, Automatic License Plate Recognition System, Engineering, Scene Text Recognition, Machine learning, Media Technology, Image (mathematics), Alphabet, Embedded system, Signature Verification, Text Detection, Real-Time Recognition, 9. Industry and infrastructure, 4. Education, 1. No poverty, Linguistics, Computer science, FOS: Philosophy, ethics and religion, Philosophy, Computer Science, Physical Sciences, 8. Economic growth, FOS: Languages and literature, Computer vision, Computer Vision and Pattern Recognition, Handwriting Recognition

An Offline Image Auditing System for Legacy Meter Reading Systems in Developing Countries: A Machine Learning Approach

Autoren: Natasha Nigar Hafiz Muhammad Faisal Muhammad Kashif Shahzad et al.

Quelle: Journal of Electrical and Computer Engineering, Vol 2022 (2022)

Schlagwörter: Artificial neural network, Computer engineering. Computer hardware, Radiology, Nuclear Medicine and Imaging, Artificial intelligence, Astronomy, FOS: Political science, Convolutional neural network, FOS: Law, Image Analysis, 02 engineering and technology, Handwriting Recognition and Text Detection, Real-time computing, TK7885-7895, Automatic License Plate Recognition System, Detection and Management of Retinal Diseases, Engineering, Reading (process), Accounting, Health Sciences, State (computer science), Media Technology, Image (mathematics), 0202 electrical engineering, electronic engineering, information engineering, Scope (computer science), Business, Metre, Political science, Chromatography, Real-Time Recognition, Sample (material), Physics, Deep learning, Audit, Computer science, ddc, Programming language, Algorithm, Operating system, Chemistry, Physical Sciences, Computer Science, Wireless, Medicine, Computer vision, Computer Vision and Pattern Recognition, Law, OCR Engine, Optical character recognition, Automatic meter reading

Dateibeschreibung: text/xhtml; application/pdf

Zugangs-URL: https://doaj.org/article/ae6f24be8361445bb90b22297f3fe32a
https://mediatum.ub.tum.de/doc/1771278/document.pdf

Enhancing automated vehicle identification by integrating YOLO v8 and OCR techniques for high-precision license plate detection and recognition

Autoren: Hanae Moussaoui Nabil El Akkad Mohamed Benslimane et al.

Quelle: Sci Rep
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)

Schlagwörter: Artificial intelligence, License, Character recognition, Science, 02 engineering and technology, Yolo v8, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Article, Automatic License Plate Recognition System, Identification (biology), Engineering, Object Detection, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Media Technology, Number Plate Detection, Biology, Image segmentation, Vehicle Identification, Botany, Deep learning, 16. Peace & justice, Computer science, OCR, Operating system, Thresholding, Physical Sciences, Computer Science, Medicine, Deep Learning in Computer Vision and Image Recognition, Computer vision, Computer Vision and Pattern Recognition, Automatic License Plate Recognition, OCR Engine

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38909147
https://doaj.org/article/50f720b779ee4fbfbaaa4409e3a0e4f8

Hybrid manifold smoothing and label propagation technique for Kannada handwritten character recognition

Autoren: Gowtham Ramesh J. Shreyas J. Balaji et al.

Quelle: Front Neurosci
Frontiers in Neuroscience, Vol 18 (2024)

Schlagwörter: Artificial neural network, Artificial intelligence, handwritten character recognition, Neurosciences. Biological psychiatry. Neuropsychiatry, Convolutional neural network, 02 engineering and technology, Speech recognition, Handwriting Recognition and Text Detection, Pattern recognition (psychology), computer vision, Automated Reconstruction of Fragmented Objects, Automatic License Plate Recognition System, Engineering, convolutional neural networks, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Media Technology, Image (mathematics), manifold smoothing, label propagation, 4. Education, Deep learning, Computer science, machine learning, Character Segmentation, Computer Science, Physical Sciences, Computer vision, Computer Vision and Pattern Recognition, Optical character recognition, RC321-571, Neuroscience, Handwriting Recognition, Smoothing

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38680450
https://doaj.org/article/2f9b41dbe3024f5c9f2df67aa8dd817a

Enhancing Unsupervised Signature Verification through Advanced Feature Extraction Techniques

Autoren: Michael Laryea Tetteh Opoku Yaw Sarfo Alex Dodoo et al.

Schlagwörter: FOS: Computer and information sciences, Signature (topology), Artificial intelligence, Feature (linguistics), Geometry, Linguistics, Statistical Machine Translation and Natural Language Processing, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Computer science, FOS: Philosophy, ethics and religion, Web Data Extraction and Crawling Techniques, Philosophy, Artificial Intelligence, Computer Science, Physical Sciences, FOS: Mathematics, FOS: Languages and literature, Feature extraction, Computer Vision and Pattern Recognition, Data mining, Mathematics, Information Systems

Impact of augmentation methods in online signature verification

Autoren: Dawid Najda Khalid Saeed

Quelle: Innovations in Systems and Software Engineering. 20:477-483

Schlagwörter: Artificial neural network, Artificial intelligence, Data set, Geometry, Set (abstract data type), 02 engineering and technology, Augmentation, Signature, Handwriting Recognition and Text Detection, Clustering of Time Series Data and Algorithms, Pattern recognition (psychology), Deep Learning, Artificial Intelligence, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Data mining, Signature Verification, Dimensionality Reduction, Signature (topology), 4. Education, Verification, Statistical Machine Translation and Natural Language Processing, Document Image Analysis, Computer science, Programming language, Biometrics, Computer Science, Physical Sciences, Signal Processing, Computer Vision and Pattern Recognition, Mathematics, Online signature, Handwriting Recognition

Dateibeschreibung: 7 páginas; application/pdf

Few shots are all you need: A progressive learning approach for low resource handwritten text recognition

Autoren: Mohamed Ali Souibgui Alícia Fornés Yousri Kessentini et al.

Quelle: Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona

Schlagwörter: FOS: Computer and information sciences, Handwriting recognition, Handwriting, Artificial intelligence, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 02 engineering and technology, Pattern recognition (psychology), Scene Text Recognition, Text Localization, Handwritten text recognition, Multi-label Text Classification in Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Similarity (geometry), Multi-label Learning, Språkteknologi (språkvetenskaplig databehandling), Text Detection, Ciphered manuscripts, encrypted manuscripts, FOS: Philosophy, ethics and religion, Programming language, Algorithm, Physical Sciences, Feature extraction, Computer Vision and Pattern Recognition, Decoding methods, Handwriting Recognition, Språkbehandling och datorlingvistik, Few-shot learning, Annotation, Set (abstract data type), Speech recognition, Handwriting Recognition and Text Detection, Mathematical analysis, Language Technology (Computational Linguistics), Bounding overwatch, Artificial Intelligence, Image (mathematics), FOS: Mathematics, Genetics, Alphabet, Biology, Unsupervised progressive learning, Natural Language Processing, Code (set theory), Domain (mathematical analysis), Natural language processing, Linguistics, Statistical Machine Translation and Natural Language Processing, Computer science, Process (computing), Philosophy, Operating system, FOS: Biological sciences, Computer Science, FOS: Languages and literature, Mathematics, Sequence (biology)

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2107.10064
https://ddd.uab.cat/record/264402
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-478941

Classification of Transformed and Geometrically Distorted Images using Convolutional Neural Network

Autoren: Sanad Aburass Ammar Huneiti Mohammad Belal Al-Zoubi

Quelle: Journal of Computer Science. 18:757-769

Schlagwörter: Artificial neural network, Artificial intelligence, Image Processing, Translation (biology), Convolutional neural network, Automated Currency Recognition and Authentication, MNIST database, 02 engineering and technology, Pattern Recognition, Handwriting Recognition and Text Detection, Pattern recognition (psychology), Fabric Defect Detection in Industrial Applications, Skewness, Biochemistry, Gene, 7. Clean energy, Industrial and Manufacturing Engineering, Feature Extraction, Engineering, Deep Learning, Image (mathematics), FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Messenger RNA, 4. Education, Statistics, Image translation, Invariant (physics), 15. Life on land, Computer science, Contextual image classification, Chemistry, 13. Climate action, Mathematical physics, Computer Science, Physical Sciences, Surface Defect Detection, Computer vision, Computer Vision and Pattern Recognition, Rotation (mathematics), Mathematics

Movie Title Extraction and Script Separation Using Shallow Convolution Neural Network

Autoren: Mridul Ghosh Sayan Saha Roy Himadri Mukherjee et al.

Quelle: IEEE Access, Vol 9, Pp 125184-125201 (2021)

Schlagwörter: Artificial intelligence, History, 02 engineering and technology, text localization, transfer learning, Pattern recognition (psychology), Automatic License Plate Recognition System, Identification (biology), Engineering, Convolution (computer science), Scene Text Recognition, Text Localization, Natural (archaeology), 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, multi-script, Text Detection, Computer graphics (images), Art history, Movie title extraction, Archaeology, Character Segmentation, Physical Sciences, 8. Economic growth, Graphics, Feature extraction, Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, Art, Artificial neural network, Geometry, Convolutional neural network, Handwriting Recognition and Text Detection, Visual arts, 12. Responsible consumption, Entertainment, Hollywood, Media Technology, Image (mathematics), FOS: Mathematics, Biology, Natural language processing, Key Frame Extraction, Botany, Orientation (vector space), Automatic Video Summarization and Analysis, 15. Life on land, Computer science, TK1-9971, 13. Climate action, Computer Science, Computer vision, Text detection, Mathematics

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09530511.pdf
https://doaj.org/article/66c932d9dc93462da6f264a84e97abd9