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Academic Articles & Research Papers
Showing 20 of 4,879 academic articles
S Yulina • Jurnal Komputer Terapan
(2021)
Aplikasi pendeteksi wajah pada citra digital sangat diperlukan dalam proses pengenalan wajah seseorang. Aplikasi ini banyak dimanfaatkan pada berbagai disiplin ilmu, salah satunya ilmu komputer visi(computer vision) seperti sistem pengenala...
DOAJ
Open Access (DOAJ)
DOI: 10.35143/jkt.v7i1.3411
Zongji Wang, Yunfei Liu, Feng Lu • Computational Visual Media
(2023)
Abstract Intrinsic image decomposition is an important and long-standing computer vision problem. Given an input image, recovering the physical scene properties is ill-posed. Several physically motivated priors have been used to restrict th...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s41095-022-0294-4
Nwankwo B, Mumueh KP, Olorukooba AA, Usman NO • Kanem Journal of Medical Sciences
(2021)
Background: Computers and other visual display devices have become essential in the present
era and have led to a rise in computer-related health problems. Using computers in homes,
universities and other institutions has increased output g...
DOAJ
Open Access (DOAJ)
DOI: 10.36020/kjms.2021.1501.003
Gustavo A. Acosta-Amaya, Deimer A. Miranda-Montoya, Jovani A. Jimenez-Builes • Sensors
(2024)
(1) Background: Human detection and tracking are critical tasks for assistive autonomous robots, particularly in ensuring safe and efficient human–robot interaction in indoor environments. The increasing need for personal assistance among t...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s24237796
Yogesh Patel, Sudeep Tanwar, Pronaya Bhattacharya, Rajesh Gupta et al. • IEEE Access
(2023)
Recent advancements in computer vision processing need potent tools to create realistic deepfakes. A generative adversarial network (GAN) can fake the captured media streams, such as images, audio, and video, and make them visually fit othe...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3251417
Arshi Parvaiz, Muhammad Anwaar Khalid, Rukhsana Zafar, Huma Ameer et al. • Engineering Applications of Artificial Intelligence
(2023)
OPENALEX
Open Access
DOI: https://doi.org/10.1016/j.engappai.2023.106126
Sebastian Nowozin • now publishers, Inc. eBooks
(2010)
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structure reflecting task-specific relations and constraints. Structu...
OPENALEX
DOI: https://doi.org/10.1561/9781601984579
Wang K, Grant JE • CNS spectrums
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1017/S1092852926101151
PMC: PMC13732604
Rose O, Clemens S, Leiherer A, Bücker M et al. • International journal of clinical pharmacy
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1007/s11096-026-02205-0
PMC: PMC13731693
Deng Q, Chen C, Zhang Q, Wei Z et al. • The clinical respiratory journal
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1111/crj.70236
PMC: PMC13731735
Vincenzo Carletti, Antonio Greco, Alessia Saggese, Bruno Vento • IEEE Access
(2026)
Automatic fire detection in video surveillance is a critical capability for safeguarding industrial sites, public infrastructures, and natural environments. Although recent advances in deep learning have substantially improved early fire de...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2026.3664195
Eda Nur Urtekin, Emre Dandıl • Journal of Agricultural Sciences
(2026)
Sustainable food production increasingly relies on intelligent automation technologies that optimize resource usage while maintaining crop health. This study presents a deep learning-driven computer vision and web based monitoring system de...
DOAJ
Open Access (DOAJ)
DOI: 10.15832/ankutbd.1817471
Asim Niaz, Sareer Ul Amin, Shafiullah Soomro, Hamza Zia et al. • IEEE Access
(2024)
Surveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods. This paper introduces an unsupervised end-t...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3435144
Lu Yuan, Dongdong Chen, Yi‐Ling Chen, Noel Codella et al. • arXiv (Cornell University)
(2021)
Automated visual understanding of our diverse and open world demands computer vision models to generalize well with minimal customization for specific tasks, similar to human vision. Computer vision foundation models, which are trained on d...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.2111.11432
Ganin, Yaroslav, Evgeniya Ustinova, Hana Ajakan, Pascal Germain et al. • Advances in computer vision and pattern recognition
(2017)
OPENALEX
DOI: https://doi.org/10.1007/978-3-319-58347-1
Zhao ZX, Yao RD, Hu ZJ, Yao Y et al. • BMC gastroenterology
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1186/s12876-026-05199-1
PMC: PMC13733082
Al-Madhagi OA, Al-Shadadi HH, Al-Hubaishi AK, Dobian SA et al. • BMC medical education
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1186/s12909-026-10106-z
PMC: PMC13733158
Khaled Abud, Sergey Lavrushkin, Dmitry Vatolin • Big Data and Cognitive Computing
(2025)
Neural-network-based models have made considerable progress in many computer vision areas over recent years. However, many works have exposed their vulnerability to malicious input data manipulation—that is, to adversarial attacks. Although...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bdcc9070166
Chuanhui Shan, Xinlong Geng, Chao Han • Heliyon
(2024)
Extracting and detecting road network consistency from high-resolution remote sensing images has been a hot and difficult problem in the computer vision. Although it has made significant progress, there is still a phenomenon of high trainin...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.heliyon.2024.e37470
Yu-wen Chen, Ju Zhang, Peng Wang, Zheng-yu Hu et al. • Frontiers in Computational Neuroscience
(2022)
Computer-assisted surgery (CAS) has occupied an important position in modern surgery, further stimulating the progress of methodology and technology. In recent years, a large number of computer vision-based methods have been widely used in ...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fncom.2022.998096