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Academic Articles & Research Papers
Showing 20 of 1,917 academic articles
Yumin Zhang, Yanyong Wang • EURASIP Journal on Image and Video Processing
(2025)
Abstract Due to the rapid advances in computer vision and deep learning, human action recognition has become one of the most important representative tasks for video understanding. Especially for human action recognition based on RGB-D data...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13640-025-00677-0
Tahiyah Nou‐Shene, Vikramkumar Pudi, K. Sridharan, Vineetha Thomas et al. • IET Computer Vision
(2015)
Autonomous vehicles engaged in terrain exploration are typically equipped with a camera. The camera is subjected to vibration as the vehicle moves so that the videos captured require stabilisation to facilitate accurate interpretation by re...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/iet-cvi.2014.0120
Eduardo D. Piedad Jr., Ricky B. Villeta • Recoletos Multidisciplinary Research Journal
(2016)
Using a camera for measurement reading is simplified through the incorporation of computer vision application. The variations in the environment’s setting, however, may constitute to the occurrence of measurement errors. A study investigate...
DOAJ
Open Access (DOAJ)
DOI: https://doi.org/10.32871/rmrj1604.01.06
Grzegorz Mrugacz, Aleksandra Mospinek, Małgorzata Jagielska, Dariusz Miszczak et al. • Biology
(2025)
Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/biology15010042
Maćkowski Michał, Sawiski Michał, Walczyszyn Wojciech • MATEC Web of Conferences
(2019)
This paper explores the effective approach to road sign detection and recognition based on mobile devices. Detecting and recognising road signs is a challenging matter because of different shapes, complex background and irregular sign illum...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/matecconf/201925203014
Suyang Xi, Zihan Liu, Ziming Wang, Qiang Zhang et al. • IEEE Access
(2024)
Lane detection is fundamental to autonomous driving, yet remains challenging in complex environments with occlusions, ambiguous markings, and varied lighting. We introduce the Global Semantic Enhancement Network (GSENet), a groundbreaking f...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3429396
Ali Haider, Ghulam Muhammad, Talha Ahmed Khan, Kushsairy Kadir et al. • Scientific Reports
(2025)
Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-18886-y
Sudeep Sarkar, Kim L. Boyer • IEEE Transactions on Systems Man and Cybernetics
(1993)
The role of perceptual organization in computer vision systems is explored. This is done from four vantage points. A brief history of perceptual organization research in both humans and computer vision is offered. A classificatory structure...
OPENALEX
DOI: https://doi.org/10.1109/21.229452
Mrs. Arjoo Pandey • International Journal for Research in Applied Science and Engineering Technology
(2023)
Abstract: Computer vision is a field of artificial intelligence that focuses on enabling computers to understand and interpret visual information from images or videos. It involves developing algorithms and techniques to extract meaningful ...
OPENALEX
Open Access
DOI: https://doi.org/10.22214/ijraset.2023.54701
Abdullah Ayub Khan, Asif Ali Laghari, Shafique Ahmad Awan • ICST Transactions on Scalable Information Systems
(2018)
INTRODUCTION: Due to the advancement in the field of Artificial Intelligence (AI), the ability to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is becoming a hot topic due to the direct training of machines...
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DOI: https://doi.org/10.4108/eai.21-4-2021.169418
(2010)
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DOI: https://doi.org/10.1109/cvpr15008.2010
Xiao Chen Yang • Journal of Physics Conference Series
(2020)
Abstract Deep convolutional neural network (CNN) plays an important role in the field of computer vision and image processing. In order to further improve the performance of CNN, scholars have conducted a series of new explorations, such as...
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DOI: https://doi.org/10.1088/1742-6596/1693/1/012173
Ke Yan, Derek Hoiem, Rahul Sukthankar • IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
(2005)
We describe how certain tasks in the audio domain can be effectively addressed using computer vision approaches. This paper focuses on the problem of music identification, where the goal is to reliably identify a song given a few seconds of...
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DOI: https://doi.org/10.1109/cvpr.2005.105
Sven Dickinson, Zygmunt Pizlo • Advances in computer vision and pattern recognition
(2013)
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DOI: https://doi.org/10.1007/978-1-4471-5195-1
Marco Alexander Treiber • Advances in computer vision and pattern recognition
(2013)
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DOI: https://doi.org/10.1007/978-1-4471-5283-5
Jiarui Bi, Zengliang Zhu, Qinglong Meng • International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI)
(2021)
Transformer is widely used in Natural Language Processing (NLP), in which numerous papers have been proposed. Recently, the transformer has been borrowed for many computer vision tasks. However, there are few papers to give a comprehensive ...
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DOI: https://doi.org/10.1109/cei52496.2021.9574462
• Kybernetes
(2001)
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DOI: https://doi.org/10.1108/k.2001.30.9_10.1333.2
• IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
(2001)
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DOI: https://doi.org/10.1109/cvpr.2001.990916
(2015)
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DOI: https://doi.org/10.1109/iccv33071.2015
Ramesh Jain, Thomas O. Binford • CVGIP Image Understanding
(1991)
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Open Access
DOI: https://doi.org/10.1016/1049-9660(91)90009-e