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Academic Articles & Research Papers
Showing 20 of 163 academic articles
Sobhana Mummaneni, Venkata Chaitanya Satya Ramaraju Mudunuri, Sri Veerabhadra Vikas Bommaganti, Bhavya Vani Kalle et al. • Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
(2025)
A facial recognition system is a biometric security and surveillance system that can identify and monitor individuals in a crowded area. Manually monitoring a crowded environment is a difficult and error-prone task. Therefore, in such conte...
DOAJ
Open Access (DOAJ)
DOI: 10.35784/iapgos.6818
Senzhang Wang, Jiannong Cao, Philip S. Yu • IEEE Transactions on Knowledge and Data Engineering
(2020)
With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temp...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.3025580
Liyan Luo, Liujun Zhang, Mei Wang, Zhenghong Liu et al. • IEEE Access
(2021)
In recent decades, surveillance and home security systems based on video analysis have been proposed for the automatic detection of abnormal situations. Nevertheless, in several real applications, it may be easier to detect a given event fr...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3123970
Shuaifeng Li, Heng Wang, Cong Zhang, Jie Liu • IEEE Access
(2022)
To address the problem that existing deep learning methods are not sufficiently accurate to detect rice pests with changeable shapes or similar appearances, a self-attention feature fusion model for rice pest detection (SAFFPest) was propos...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2022.3194925
Nitin Kumar Chauhan, Krishna Pal Singh • International Conference on Computing, Power and Communication Technologies (GUCON)
(2018)
In now days, deep learning has become a prominent and emerging research area in computer vision applications. Deep learning permits the multiple layers models for computation to learn representations of data by processing in their original ...
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DOI: https://doi.org/10.1109/gucon.2018.8675097
Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan K.E. Westberg et al. • Electronics
(2019)
In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some ne...
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DOI: https://doi.org/10.3390/electronics8030292
Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du et al. • BMC Bioinformatics
(2019)
Abstract Background Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural n...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12859-019-2617-8
Abderrazak Khediri, Ayoub Yahiaoui, Mohamed Ridda Laouar, Yacine Belhocine • Acta Informatica Pragensia
(2024)
Blackout events in smart grids can have significant impacts on individuals, communities and businesses, as they can disrupt the power supply and cause damage to the grid. In this paper, a new proactive approach to an early warning system fo...
DOAJ
Open Access (DOAJ)
DOI: 10.18267/j.aip.246
Konstantinos Keremis, Eleni Vrochidou, George A. Papakostas • Journal of Imaging
(2025)
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/jimaging11090322
Guangyu Zhu, Xueqi Luo, Tingting Yang, Li Cai et al. • Frontiers in Physiology
(2022)
The manual identification and segmentation of intracranial aneurysms (IAs) involved in the 3D reconstruction procedure are labor-intensive and prone to human errors. To meet the demands for routine clinical management and large cohort studi...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fphys.2022.1084202
Andrew J. Reader, Guillaume Corda-D’Incan, Abolfazl Mehranian, Casper O. da Costa-Luis et al. • IEEE Transactions on Radiation and Plasma Medical Sciences
(2020)
This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for the reconstruction of images in positron emission tomography (PET). Deep learning can be used either directly or as a component of conventio...
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Open Access
DOI: https://doi.org/10.1109/trpms.2020.3014786
Phillip M. Cheng, Emmanuel Montagnon, Rikiya Yamashita, Ian Pan et al. • Radiographics
(2021)
Deep learning is a class of machine learning methods that has been successful in computer vision. Unlike traditional machine learning methods that require hand-engineered feature extraction from input images, deep learning methods learn the...
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DOI: https://doi.org/10.1148/rg.2021200210
Yuying Zhang, Fei Xu, Yi Yang • Applied Sciences
(2025)
In recent years, gaze estimation has received a lot of interest in areas including human–computer interface, virtual reality, and user engagement analysis. Despite significant advances in convolutional neural network (CNN) techniques, direc...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app152312475
Xiaojiao Chen, Xiuqing Zhang, Mi Dong, Liansheng Huang et al. • Frontiers in Energy Research
(2021)
The prediction of wind power plays an indispensable role in maintaining the stability of the entire power grid. In this paper, a deep learning approach is proposed for the power prediction of multiple wind turbines. Starting from the time s...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fenrg.2021.723775
Mingyu Zhao, Shujia Zhang, Ke Li, Yanru Zhang et al. • Frontiers in Robotics and AI
(2026)
Densely populated enclosed environments, characterized by complex thermal stratification and overlapping breathing zones, represent high-risk clusters for the airborne transmission of respiratory pathogens. To address the dual challenges of...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/frobt.2026.1846010
Xiaofei Yang, Yunming Ye, Xutao Li, Raymond Y.K. Lau et al. • IEEE Transactions on Geoscience and Remote Sensing
(2018)
Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem. In contrast to conventional computer vision task...
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DOI: https://doi.org/10.1109/tgrs.2018.2815613
Mihalj Bakator, Dragica Radosav • Multimodal Technologies and Interaction
(2018)
In this review the application of deep learning for medical diagnosis is addressed. A thorough analysis of various scientific articles in the domain of deep neural networks application in the medical field has been conducted. More than 300 ...
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DOI: https://doi.org/10.3390/mti2030047
S. Chinnadurai, S. Selvakumar • Scientific Reports
(2025)
Abstract Cotton has, in recent years, become one of the most important cash crops worldwide while being impacted in yield from leaf disease which generally goes unnoticed in the early stage. Detection methods depend on manual efforts produc...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-28549-7
Jaya Gupta, Sunil Kumar Pathak, Gireesh Kumar • Journal of Physics Conference Series
(2022)
Abstract Deep Learning is a machine learning area that has recently been used in a variety of industries. Unsupervised, semi-supervised, and supervised-learning are only a few of the strategies that have been developed to accommodate differ...
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DOI: https://doi.org/10.1088/1742-6596/2273/1/012029
XIAO Zhipeng, HE Shufeng, TIAN Chunqi • Jisuanji gongcheng
(2025)
This study presents a facial emotion recognition network based on UniRepLKNet to address the difficulty in effectively capturing feature information and preventing key facial information from occupying a more prominent position in the facia...
DOAJ
Open Access (DOAJ)
DOI: 10.19678/j.issn.1000-3428.0069761