Suchergebnisse - Human-computer integration. Computer vision. Pattern recognition systems. Image processing*

Residual Connection Networks in Medical Image Processing: Exploration of ResUnet++ Model Driven by Human Computer Interaction

Autoren: Dai, Peixin Zhang, Jingsi Shu, Zhitao

Quelle: Applied and Computational Engineering. 116:194-199

Schlagwörter: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing

Zugangs-URL: http://arxiv.org/abs/2412.20709

Towards human-AI collaboration system for the detection of invasive ductal carcinoma in histopathology images

Autoren: Shuo Han Ahmed Karam Eldaly Solomon Sunday Oyelere

Quelle: Human-Intelligent Systems Integration.

Schlagwörter: Human-Computer Interaction, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, Image and Video Processing, Computer Vision and Pattern Recognition, Human-Computer Interaction (cs.HC)

Zugangs-URL: http://arxiv.org/abs/2508.07875

HistoColAi: An open-source web platform for collaborative digital histology image annotation with AI-driven predictive integration

Autoren: Cristian Camilo Pulgarín-Ospina Rocío del Amor Julio José Silva-Rodríguez et al.

Quelle: Computer Methods and Programs in Biomedicine. 260:108577

Schlagwörter: FOS: Computer and information sciences, Internet, Skin Neoplasms, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Human-Computer Interaction, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing, 3. Good health, Human-Computer Interaction (cs.HC), Deep Learning, Artificial Intelligence, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, FOS: Electrical engineering, electronic engineering, information engineering, Humans, Diagnosis, Computer-Assisted, Software

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39813900
http://arxiv.org/abs/2307.07525

Digital Health Transformation, Smart Ageing, and Managing Disability

Autoren: Kim Jongbae Mounir Mokhtari Hamdi Aloulou et al.

Resource Type: eBook.

Schlagworte: Computer networks, Software engineering, Application software, Artificial intelligence--Medical applications--Congresses, Medical telematics--Congresses, Medical technology--Congresses, User interfaces (Computer systems), Image processing--Digital techniques, Computer vision, Computer systems

Categories: COMPUTERS / Networking / General, COMPUTERS / Business & Productivity Software / General, COMPUTERS / Computer Architecture, COMPUTERS / Image Processing, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Software Development & Engineering / General, COMPUTERS / Hardware / General, COMPUTERS / User Interfaces, COMPUTERS / Human-Computer Interaction (HCI)

Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)

Autoren: Ramesh Manza Bharti Gawali Pravin Yannawar et al.

Resource Type: eBook.

Schlagworte: Artificial intelligence--Congresses, Computer vision--Congresses

Categories: COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Image Processing, MATHEMATICS / Probability & Statistics / General

Inference-Time Gaze Refinement for Micro-Expression Recognition: Enhancing Event-Based Eye Tracking with Motion-Aware Post-Processing

Autoren: Bandara, Nuwan Kandappu, Thivya Misra, Archan

Schlagwörter: Human-Computer Interaction, Machine Learning, FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, Image and Video Processing, Computer Vision and Pattern Recognition, Human-Computer Interaction (cs.HC), Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2506.12524

Advances in Computer Vision and Deep Learning and Its Applications.

Autoren: Wang, Aili Wu, Haibin Iwahori, Yuji

Quelle: Electronics (2079-9292); Apr2025, Vol. 14 Issue 8, p1551, 19p

Schlagwörter: ARTIFICIAL neural networks, ARTIFICIAL intelligence, PATTERN recognition systems, COMPUTER vision, CONVOLUTIONAL neural networks, DEEP learning, INTELLIGENT transportation systems

Evaluation of Benchmark Datasets and Deep Learning Models with Pre-Trained Weights for Vision-Based Dynamic Hand Gesture Recognition.

Autoren: Yaseen Kwon, Oh-Jin Kim, Jaeho et al.

Quelle: Applied Sciences (2076-3417); Jun2025, Vol. 15 Issue 11, p6045, 25p

Schlagwörter: ARTIFICIAL intelligence, PATTERN recognition systems, CLASSIFICATION algorithms, TRANSFORMER models, COMPUTER systems, DEEP learning, COMPUTER vision

Editorial: Advances in computer vision: from deep learning models to practical applications.

Autoren: Zhu, Hancheng Yao, Rui Tang, Lu

Quelle: Frontiers in Neuroscience; 2025, p1-3, 3p

Schlagwörter: AFFECTIVE computing, COMPUTER vision, PATTERN recognition systems, OBJECT recognition (Computer vision), HUMAN facial recognition software, EMOTION recognition, SIGNAL convolution

Computer Vision-Based Gait Recognition on the Edge: A Survey on Feature Representations, Models, and Architectures.

Autoren: Salcedo, Edwin

Quelle: Journal of Imaging; Dec2024, Vol. 10 Issue 12, p326, 38p

Schlagwörter: PATTERN recognition systems, COMPUTER vision, EDGE computing, ARTIFICIAL intelligence, PERSONAL computers

An integrated attention-guided deep convolutional neural network for facial expression recognition in the wild.

Autoren: Saurav, Sumeet Saini, Ravi Singh, Sanjay

Quelle: Multimedia Tools & Applications; Apr2025, Vol. 84 Issue 12, p10027-10069, 43p

Schlagwörter: CONVOLUTIONAL neural networks, PATTERN recognition systems, ARTIFICIAL intelligence, INFORMATION storage & retrieval systems, COMPUTER vision

HDMA-CGAN: Advancing Image Style Transfer with Deep Learning.

Autoren: Liu, Huaqun Hu, Benxi Cao, Yu

Quelle: International Journal of Pattern Recognition & Artificial Intelligence; Jul2024, Vol. 38 Issue 9, p1-27, 27p

Schlagwörter: DEEP learning, PATTERN recognition systems, GENERATIVE adversarial networks, COMPUTER vision, ARTIFICIAL intelligence, TRANSFER of training

A Survey of Multimodal Learning: Methods, Applications, and Future.

Autoren: Yuan, Yuan Li, Zhaojian Zhao, Bin

Quelle: ACM Computing Surveys; Jul2025, Vol. 57 Issue 7, p1-34, 34p

Schlagwörter: PATTERN recognition systems, ARTIFICIAL intelligence, LANGUAGE models, COMPUTER vision, AUDITORY scene analysis

Recent developments on neuromorphic optoelectronic memristors based on metal oxide semiconductors: A review.

Autoren: Shrivastava, Saransh Juliano, Hans Uong, Phan Ai Linh et al.

Quelle: APL Electronic Devices; Jun2025, Vol. 1 Issue 2, p1-37, 37p

Schlagwörter: ARTIFICIAL neural networks, METAL oxide semiconductors, PATTERN recognition systems, MEMRISTORS, IMAGE recognition (Computer vision)

Digits Recognition for Arabic Handwritten through Convolutional Neural Networks, Local Binary Patterns, and Histogram of Oriented Gradients.

Alternate Title: التعرف على الأرقام للغة العربية المكتوبة بخط اليد من خلال الشبكات العصبية التلافيفية والأنماط الثنائية المحلية والرسم البياني للتدرجات الموجهة. (Arabic)

Autoren: Hasan, Bushra Mahdi Jaber, Zahraa Jasim Habeeb, Ahmad Adel

Quelle: Baghdad Science Journal; 2024, Vol. 21 Issue 10, p3322-3332, 11p

Schlagwörter: PATTERN recognition systems, OBJECT recognition (Computer vision), COMPUTER vision, CONVOLUTIONAL neural networks, FEATURE extraction, HANDWRITING recognition (Computer science)

Automatic human age estimation from face images using MLP and RBF neural network algorithms in secure communication networks.

Autoren: ALRikabi, Haider TH. Salim Assad, Ali Al Dujaili, Mohammed Jawad et al.

Quelle: Sustainable Engineering & Innovation; Dec2024, Vol. 6 Issue 2, p185-198, 14p

Schlagwörter: MULTILAYER perceptrons, PATTERN recognition systems, COMPUTER vision, INDEPENDENT component analysis, FORENSIC sciences

JaneEye: A 12-nm 2K-FPS 18.9-$μ$J/Frame Event-based Eye Tracking Accelerator

Autoren: Han, Tao Li, Ang Chen, Qinyu et al.

Schlagwörter: Hardware Architecture, Human-Computer Interaction, Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Signal Processing, Hardware Architecture (cs.AR), Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, Image and Video Processing, Computer Vision and Pattern Recognition, Human-Computer Interaction (cs.HC)

Zugangs-URL: http://arxiv.org/abs/2510.01213

Innovating physical education with artificial intelligence: a potential approach.

Autoren: Cui, Bin Jiao, Wei Gui, Shuying et al.

Quelle: Frontiers in Psychology; 2025, p1-5, 5p

Schlagwörter: MACHINE learning, IMAGE recognition (Computer vision), COMPUTER vision, ARTIFICIAL neural networks, PATTERN recognition systems, SPORTS participation

Automating attendance management in human resources: A design science approach using computer vision and facial recognition

Autoren: Bao-Thien Nguyen-Tat Minh-Quoc Bui Vuong M. Ngo

Quelle: International Journal of Information Management Data Insights, Vol 4, Iss 2, Pp 100253-(2024)

Schlagwörter: Embedded computer, FOS: Computer and information sciences, Computer Science - Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), 4. Education, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction, Information technology, Systems and Control (eess.SY), T58.5-58.64, Electrical Engineering and Systems Science - Systems and Control, Human-Computer Interaction (cs.HC), 3. Good health, Artificial Intelligence (cs.AI), Machine learning, Hardware Architecture (cs.AR), 8. Economic growth, FOS: Electrical engineering, electronic engineering, information engineering, Attendance management system, Face recognition, Computer Science - Hardware Architecture, 10. No inequality, Haar cascade classification

Zugangs-URL: http://arxiv.org/abs/2405.12633
https://doaj.org/article/d165acbde5964c74ace7c0e3595424cb

Augmented reality safety warnings in roadway work zones: Evaluating the effect of modality on worker reaction times

Autoren: Sepehr Sabeti Fatemeh Banani Ardecani Omidreza Shoghli

Quelle: Transportation Research Part C: Emerging Technologies. 169:104867

Schlagwörter: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Human-Computer Interaction, Computer Science - Computer Vision and Pattern Recognition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, Human-Computer Interaction (cs.HC)

Zugangs-URL: http://arxiv.org/abs/2403.15571