Suchergebnisse - "Computer Vision - Machine Learning"

GTA-HDR: A Large-Scale Synthetic Dataset for HDR Image Reconstruction

Autoren: Barua, Hrishav Bakul Stefanov, Kalin Wong, KokSheik et al.

Quelle: 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). :7876-7886

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, I.3.3, I.4.5, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, Artificial intelligence, Computer vision, Machine learning, Deep learning, Electrical Engineering and Systems Science - Image and Video Processing, Graphics (cs.GR), Machine Learning (cs.LG), Multimedia (cs.MM), Computer Science - Graphics, FOS: Electrical engineering, electronic engineering, information engineering, Computer Science - Multimedia

Zugangs-URL: http://arxiv.org/abs/2403.17837

Facial Asymmetry Classification in Neurological Disorders: Integrating Computer Vision and Machine Learning for Improved Patient Care

Autoren: Ranjan, Pratik Lasala, Angelo Ruscelli, Anna Lina et al.

Quelle: 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI). :196-201

Schlagwörter: Facial Palsy, Stroke, Artificial Intelligence, Computer Vision, Machine learning, Face Tracking, Asymmetry, Neurological Disorder

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11564/844313
https://doi.org/10.1109/rtsi61910.2024.10761311
https://ieeexplore.ieee.org/document/10761311
https://doi.org/10.1109/RTSI61910.2024.10761311
https://hdl.handle.net/11382/571940

Histohdr-Net: Histogram Equalization for Single LDR to HDR Image Translation

Autoren: Barua, Hrishav Bakul Krishnasamy, Ganesh Wong, KokSheik et al.

Quelle: 2024 IEEE International Conference on Image Processing (ICIP). :2730-2736

Schlagwörter: Computer Science - Machine Learning, Computer Science - Graphics, I.3.3, Computer Science - Artificial Intelligence, I.4.5, Computer Science - Computer Vision and Pattern Recognition, Artificial intelligence, Computer vision, Machine learning, Deep learning, Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Multimedia

Zugangs-URL: http://arxiv.org/abs/2402.06692

Deep panoramic depth prediction and completion for indoor scenes

Autoren: Pintore G. Almansa E. Sanchez A. et al.

Quelle: Computational Visual Media. 10:903-922

Schlagwörter: 3D stereo scene analysis, image processing and computer vision, machine learning, vision, scene understanding, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11379/592675
https://doi.org/10.1007/s41095-023-0358-0

Smart Pot: An Intelligent Plant Care Assistant

Autoren: Ayush Baiju Binoy C E Joseph Alvis Sajith et al.

Schlagwörter: IoT, Computer vision, Machine learning, Plant disease detection, Yolov5

DEVELOPMENT OF A MODEL FOR RECOGNIZING VARIOUS OBJECTS AND TOOLS IN A COLLABORATIVE ROBOT WORKSPACE

Autoren: Yevsieiev, V. Amer Abu-Jassar Maksymova, S. et al.

Schlagwörter: Object Recognition, Robotic Systems, Object Recognition, Robotic Systems, Computer Vision, Machine Learning, Robot Workspace, Industry 5.0

Dateibeschreibung: application/pdf

PhysHDR: When Lighting Meets Materials and Scene Geometry in HDR Reconstruction

Autoren: Barua, Hrishav Bakul Stefanov, Kalin Krishnasamy, Ganesh et al.

Schlagwörter: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), I.3.3, I.4.5, Artificial intelligence, Computer vision, Machine learning, Deep learning, Image and Video Processing, Graphics (cs.GR), Machine Learning (cs.LG), Multimedia (cs.MM), Machine Learning, Artificial Intelligence (cs.AI), Multimedia, Artificial Intelligence, FOS: Electrical engineering, electronic engineering, information engineering, Graphics, Computer Vision and Pattern Recognition

Zugangs-URL: http://arxiv.org/abs/2509.16869

MD-BERT: Action Recognition in Dark Videos via Dynamic Multi-Stream Fusion and Temporal Modeling

Autoren: Dass, Sharana Dharshikgan Suresh Barua, Hrishav Bakul Krishnasamy, Ganesh et al.

Schlagwörter: I.2, FOS: Computer and information sciences, I.2.9, I.2.10, I.3.3, I.4.5, Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction, Human-Computer Interaction (cs.HC), Machine Learning (cs.LG), Multimedia (cs.MM), Artificial Intelligence (cs.AI), Artificial intelligence, Computer vision, Machine learning, Deep learning, Human-computer Interaction, Computer Science - Multimedia

Zugangs-URL: http://arxiv.org/abs/2502.03724

ActNetFormer: Transformer-ResNet Hybrid Method for Semi-supervised Action Recognition in Videos

Autoren: Dass, Sharana Dharshikgan Suresh Barua, Hrishav Bakul Krishnasamy, Ganesh et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783031783531

Schlagwörter: I.2, FOS: Computer and information sciences, I.2.9, I.2.10, I.3.3, I.4.5, Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction, Human-Computer Interaction (cs.HC), Machine Learning (cs.LG), Multimedia (cs.MM), Artificial Intelligence (cs.AI), Artificial intelligence, Computer vision, Machine learning, Deep learning, Human-computer Interaction, Computer Science - Multimedia

Zugangs-URL: http://arxiv.org/abs/2404.06243

Length-Aware Motion Synthesis via Latent Diffusion

Autoren: Alessio Sampieri Alessio Palma Indro Spinelli et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783031736674

Schlagwörter: computer vision, machine learning, generative artificial intelligence, motion synthesis, FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition

Zugangs-URL: http://arxiv.org/abs/2407.11532

Визуальный подход к образованию в эпоху информационного перенасыщения: концепция новой словарно-энциклопедической модели (Visual approach to education in the era of information overload: А new dictionary-encyclopedic model concept)

Autoren: Aleksey Pogrebnoj-Alexandroff

Schlagwörter: Educational technology and computing, Artificial intelligence not elsewhere classified, Computer vision, Computer vision and multimedia computation not elsewhere classified, Library and information studies not elsewhere classified, Educational technology, Образовательные технологии, Artificial intelligence, Artificial intelligence -- Educational applications, Artificial intelligence (AI) in education, Artificial Intelligence and image processing, Artificial Intelligence & Higher-Dimensional Learning, Artificial intelligence (AI) evaluation, Artificial Intelligence (A.I.), Artificial intelligence -- Industrial applications, Artificial Intelligence (AI) in Healthcare, Artificial Intelligence & MOOCs, Artificial Intelligence & Writing, Искусственный интеллект, Computer vision -- Mathematical models, computer vision advances, computer vision approaches, Computer Vision & Image Processing - Pattern Recognition, Computer Vision - Machine Learning, Computer Vision - Recognition, Computer vision -- Mathematics, computer vision classification, Computer vision development, computer vision classifiers, Computer Vision & Image Processing - 3D

Verfügbarkeit: https://doi.org/10.6084/m9.figshare.30015580.v1
https://figshare.com/articles/online_resource/____________-____Visual_approach_to_education_in_the_era_of_information_overload_new_dictionary-encyclopedic_model_concept_/30015580

Distance-based Loss Function for Machine Learning in Image Segmentation of Concrete Cracks

Autoren: Özcan, Baris Schmiedecke, Fabian Alexander

Schlagwörter: Machine Learning, Computer Vision, Loss Functions, Concrete Crack Detection | Computer Vision | Machine Learning | Image Segmentation | Loss Functions, Technology::621: Applied Physics::621.3: Electrical Engineering, Electronic Engineering, Concrete Crack Detection, Image Segmentation, Technology::624: Civil Engineering, Environmental Engineering, Technology::620: Engineering

REAL-TIME OBJECT DETECTION AND CLASSIFICATION IN VIDEO IMAGES USING NEURAL NETWORKS

Autoren: Muminov Islom

Schlagwörter: Real-time object detection, video classification, neural networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), computer vision, machine learning

EXPLORING MOTION CAPTURE ALGORITHMS IN COMPUTER VISION USING INTEL DEPTH CAMERA

Autoren: Ollaberganova, Muyassar

Schlagwörter: motion capture, virtual reality, triangulation, computer vision, machine learning

EXPLORING MOTION CAPTURE ALGORITHMS IN COMPUTER VISION USING INTEL DEPTH CAMERA

Autoren: M.D.Ollaberganova T.A. Xudaybergenov

Schlagwörter: virtual reality, motion capture, virtual reality, triangulation, computer vision, machine learning

Architect, Regularize and Replay: A Flexible Hybrid Approach for Continual Learning

Autoren: Vincenzo Lomonaco Lorenzo Pellegrini Gabriele Graffieti et al.

Quelle: Towards Human Brain Inspired Lifelong Learning ISBN: 9789811286704

Schlagwörter: Continual Learning, FOS: Computer and information sciences, Computer Science - Machine Learning, Lifelong Learning, Computer Science - Artificial Intelligence, Computer Vision, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing, Continual Learning, Lifelong Learning, Computer Vision, Machine Learning, Artificial Intelligence, 02 engineering and technology, Machine Learning (cs.LG), Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Artificial Intelligence (cs.AI), Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, Neural and Evolutionary Computing (cs.NE)

Zugangs-URL: http://arxiv.org/abs/2301.02464

'Bridging the gap': A Survey of Sign Language Interpretation Technologies

Autoren: Ajay Rajendran Abhiraj B Akash S et al.

Schlagwörter: Sign language interpretation, Computer vision, Machine learning, Artificial intelligence algorithms

Comprehensive Approach to Drone-Based Number Plate Recognition Using Python

Autoren: Swamy, Samatha R Pushpa, G Gowda, Mithun G R et al.

Schlagwörter: Number Plate Acknowledgment, Programmed Permit Plate Acknowledgment, Python, Computer Vision, Machine Learning, Profound Learning, Picture Preparing, 16. Peace & justice

Yoga Pose Images Name Detection using Random Forest

Autoren: Sanila Sunny T J Jobin

Schlagwörter: Yoga pose recognition, Computer vision, Machine learning, MediaPipe, Pose estimation, Random Forest classifier, scikit-learn, Image processing, Model evaluation, Model deployment

Effective Deployment of CNNs for 3DoF Pose Estimation and Grasping in Industrial Settings

Autoren: de Gregorio D. Zanella R. Palli G. et al.

Quelle: 25th International Conference on Pattern Recognition, ICPR 2020
2020 25th International Conference on Pattern Recognition (ICPR)

Schlagwörter: FOS: Computer and information sciences, Computer Science - Robotics, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 0202 electrical engineering, electronic engineering, information engineering, Computer Vision Machine Learning, 02 engineering and technology, Robotics (cs.RO)

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/pdf/2012.13210
http://arxiv.org/abs/2012.13210
https://dblp.uni-trier.de/db/conf/icpr/icpr2020.html#GregorioZPS20
https://ieeexplore.ieee.org/document/9411912
https://doi.org/10.1109/ICPR48806.2021.9411912
https://hdl.handle.net/11585/841335