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Academic Articles & Research Papers
Showing 20 of 88 academic articles
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
Yudong Zhang, Lijia Deng, Hengde Zhu, Wei Wang et al. • Information Fusion
(2023)
Integrating artificial intelligence with food category recognition has been a field of interest for research for the past few decades. It is potentially one of the next steps in revolutionizing human interaction with food. The modern advent...
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DOI: https://doi.org/10.1016/j.inffus.2023.101859
Roger Alves de Oliveira, Math Bollen • Electric Power Systems Research
(2022)
This paper aims to introduce deep learning to the power quality community by reviewing the latest applications and discussing the open challenges of this technology. Publications covering deep learning to power quality are stratified in ter...
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DOI: https://doi.org/10.1016/j.epsr.2022.108887
N. Kannaiya Raja, E. Laxmi Lydia, Thumpala Archana Acharya, K. Radhika et al. • IEEE Access
(2023)
In recent years, drones or Unmanned Aerial Vehicles (UAVs) got significant attention among researchers because of their extensive application in commercial applications, border surveillance, etc. As the conventional terrestrial communicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3324068
Michele Avanzo, Lise Wei, Joseph Stancanello, Martin Vallières et al. • Medical Physics
(2020)
Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and biological endpoints. The development of quantitative imaging methods along with machine learning has...
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DOI: https://doi.org/10.1002/mp.13678
PMC: 8965689
saeedeh zebhi, Seyed Mohammad Taghi AlModaressi, Vahid Abootalebi • AUT Journal of Electrical Engineering
(2021)
In this paper, two different methods of human activity recognition based on video signals are introduced. The first method explores the effectiveness of combining feature descriptors obtained by local descriptors and artificial neural network ...
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Open Access (DOAJ)
DOI: 10.22060/eej.2020.18517.5357
Xuedan Du, Yinghao Cai, Shuo Wang, Leijie Zhang • Youth Academic Annual Conference of Chinese Association of Automation (YAC)
(2016)
In recent years, deep learning has achieved great success in many fields, such as computer vision and natural language processing. Compared to traditional machine learning methods, deep learning has a strong learning ability and can make be...
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DOI: https://doi.org/10.1109/yac.2016.7804882
Gabriel Chartrand, Phillip M. Cheng, Eugene Vorontsov, Michal Drozdzal et al. • Radiographics
(2017)
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods prod...
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DOI: https://doi.org/10.1148/rg.2017170077
Shiyao Duan, Jiaojiao Li, Rui Song, Yunsong Li et al. • Remote Sensing
(2023)
Deep learning networks based on CNNs or transformers have made progress in spectral reconstruction (SR). However, many methods focus solely on feature extraction, overlooking the interpretability of network design. Additionally, models excl...
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Open Access (DOAJ)
DOI: 10.3390/rs15102619
Beatriu Reig, Laura C. Heacock, Krzysztof J. Geras, Linda P. Moy • Journal of Magnetic Resonance Imaging
(2019)
Machine-learning techniques have led to remarkable advances in data extraction and analysis of medical imaging. Applications of machine learning to breast MRI continue to expand rapidly as increasingly accurate 3D breast and lesion segmenta...
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DOI: https://doi.org/10.1002/jmri.26852
PMC: 7085409
S. Vijayan, Chiranji Lal Chowdhary • Scientific Reports
(2025)
Abstract The agricultural industry significantly relies on autonomous systems for detecting and analyzing rice diseases to minimize financial and resource losses, reduce yield reductions, improve processing efficiency, and ensure healthy cr...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-92646-w
Xiuhua April Si, Jinxiang Xi • Journal of Nanotheranostics
(2021)
Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challengin...
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Open Access (DOAJ)
DOI: 10.3390/jnt2030007
Sumesh Kharnotia, Bhavna Arora, Ravdeep Kour • ICT Express
(2026)
The extensive embrace of Android has amplified malware risks, resulting in a need for better detection methods. This article investigates the area of static analysis, which analyses applications without execution by examining code and manif...
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Open Access (DOAJ)
DOI: 10.1016/j.icte.2026.01.005
Shivi Garg, Niyati Baliyan • Data in Brief
(2019)
The data in this article have been collaborated from mainly four sources- Google Playstore,11 Google Playstore https://play.google.com/store/apps. Wandoujia22 Wandoujia apps http://www.wandoujia.com/apps. (third party app store market), AMD...
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Open Access (DOAJ)
DOI: 10.1016/j.dib.2018.12.038
Xiangyu Liu, Yi Han, Yanhui Du • Sensors
(2022)
With the large-scale application of the Internet of Things (IoT), security issues have become increasingly prominent. Device identification is an effective way to secure IoT environment by quickly identifying the category or model of device...
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Open Access (DOAJ)
DOI: 10.3390/s22218337
Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang et al. • Applied Sciences
(2025)
The extraction of shape features from vector elements is essential in cartography and geographic information science, supporting a range of intelligent processing tasks. Traditional methods rely on different machine learning algorithms tail...
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Open Access (DOAJ)
DOI: 10.3390/app15052383
Elisabeth Källström, Tomas Olsson, John Lindström, Lars Hakansson et al. • International Journal of Prognostics and Health Management
(2018)
In order to reduce unnecessary stops and expensive downtime originating from clutch failure of construction equipment machines; adequate real time sensor data measured on the machine in combination with feature extraction and classification...
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Open Access (DOAJ)
DOI: doi:10.36001/ijphm.2018.v9i1.2693
Michela Prunella, Roberto Maria Scardigno, Domenico Buongiorno, Antonio Brunetti et al. • IEEE Access
(2023)
Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3271748
Felix Menne, Felix Dörr, Julia Schräder, Johannes Tröger et al. • BMC Psychiatry
(2024)
Abstract Background Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patient...
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Open Access (DOAJ)
DOI: 10.1186/s12888-024-06253-6
Tarik Abu-Ain, Siti Norul Huda Sheikh Abdullah, Khairuddin Omar, Ashraf Abu-Ein et al. • Journal of ICT Research and Applications
(2014)
Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, t...
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Open Access (DOAJ)
DOI: 10.5614/itbj.ict.res.appl.2013.7.2.5