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Academic Articles & Research Papers
Showing 20 of 169 academic articles
Swarnendu Ghosh, Nibaran Das, Ishita Das, Ujjwal Maulik • ACM Computing Surveys
(2019)
The machine learning community has been overwhelmed by a plethora of deep learning--based approaches. Many challenging computer vision tasks, such as detection, localization, recognition, and segmentation of objects in an unconstrained envi...
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Open Access
DOI: https://doi.org/10.1145/3329784
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
Zijian Wang, Haimei Lu, Haixin Yan, Hongxing Kan et al. • Scientific Reports
(2023)
Abstract Diabetic Retinopathy (DR) is a major cause of blindness worldwide. Early detection and treatment are crucial to prevent vision loss, making accurate and timely diagnosis critical. Deep learning technology has shown promise in the a...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-023-38320-5
Mingyu Kim, Jihye Yun, Yongwon Cho, Keewon Shin et al. • Neurospine
(2019)
The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learn...
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cc-by-nc
DOI: https://doi.org/10.14245/ns.1938396.198
PMC: 6945006
Alexander Selvikvåg Lundervold, Arvid Lundervold • Zeitschrift für Medizinische Physik
(2018)
What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when...
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DOI: https://doi.org/10.1016/j.zemedi.2018.11.002
Jiaxi Tang, Yaqin Zhao, Liqi Feng, Wenxuan Zhao • Animals
(2022)
Camera traps are widely used in wildlife research, conservation, and management, and abundant images are acquired every day. Efficient real-time instance segmentation networks can help ecologists label and study wild animals. However, exist...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/ani12151980
Intisar Rizwan I Haque, Jeremiah J. Neubert • Informatics in Medicine Unlocked
(2020)
The review covers automatic segmentation of images by means of deep learning approaches in the area of medical imaging. Current developments in machine learning, particularly related to deep learning, are proving instrumental in identificat...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.imu.2020.100297
Shervin Minaee, Yuri Y. Boykov, Fatih Porikli, Antonio Plaza et al. • IEEE Transactions on Pattern Analysis and Machine Intelligence
(2021)
Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, amon...
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Open Access
DOI: https://doi.org/10.1109/tpami.2021.3059968
Lijian Zhang, Guangfu Liu • Advances in Mathematical Physics
(2021)
Ceramic image shape 3D image modeling focuses on of ceramic that was obtained from the camera imaging equipment such as 2D images, by normalization, gray, filtering denoising, wavelet image sharpening edge enhancement, binarization, and sha...
DOAJ
Open Access (DOAJ)
DOI: 10.1155/2021/4343255
Shengfeng Liu, Yi Wang, Xin Yang, Baiying Lei et al. • Engineering
(2019)
Ultrasound (US) has become one of the most commonly performed imaging modalities in clinical practice. It is a rapidly evolving technology with certain advantages and with unique challenges that include low imaging quality and high variabil...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.eng.2018.11.020
Chen Chen, Chen Qin, Huaqi Qiu, Giacomo Tarroni et al. • Frontiers in Cardiovascular Medicine
(2020)
Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalit...
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DOI: https://doi.org/10.3389/fcvm.2020.00025
PMC: 7066212
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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other-oa
DOI: https://doi.org/10.1002/mp.13678
PMC: 8965689
Wei Zhang, Chao Ren, Haoming Bai, Huada Huang et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2026)
Accurate monitoring of the spatial extent of sugarcane cultivation is critical for optimizing land-use efficiency and regulating the sugar industry. However, sugarcane cultivation areas are characterized by complex topography and fragmented...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2026.3716367
Gustau Camps‐Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein • Wiley eBooks
(2021)
Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only re...
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Open Access
DOI: https://doi.org/10.1002/9781119646181
Marco Paracchini, Marco Marcon, Federica Villa, Franco Zappa et al. • Sensors
(2020)
The problem of performing remote biomedical measurements using just a video stream of a subject face is called remote photoplethysmography (rPPG). The aim of this work is to propose a novel method able to perform rPPG using single-photon av...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s20216102
Johannes L. Otto, Lukas M. Sauer, Malte Brink, Thorge Schaum et al. • Materials & Design
(2023)
Nickel-based filler metals are frequently used in high temperature vacuum diffusion brazing for austenitic stainless-steel joints when components are subjected to high static or dynamic loads, corrosive environments and elevated temperature...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.matdes.2023.112401
Theodore Spaide, PhD, Anand E. Rajesh, MD, Nayoon Gim, Marian Blazes, MD et al. • Ophthalmology Science
(2025)
Purpose: To apply methods for quantifying uncertainty of deep learning segmentation of geographic atrophy (GA). Design: Retrospective analysis of OCT images and model comparison. Participants: One hundred twenty-six eyes from 87 participant...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.xops.2024.100587
Yu Lyu, Xiaolin Tian • Bioengineering
(2023)
Deep learning technology has achieved breakthrough research results in the fields of medical computer vision and image processing. Generative adversarial networks (GANs) have demonstrated a capacity for image generation and expression abili...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bioengineering10091091
Srigiri Krishnapriya, Yepuganti Karuna • Frontiers in Oncology
(2024)
IntroductionBrain tumors are a common disease that affects millions of people worldwide. Considering the severity of brain tumors (BT), it is important to diagnose the disease in its early stages. With advancements in the diagnostic process...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fonc.2024.1347363
Dinggang G. Shen, Guorong Wu A, Heung‐Il Suk • Annual Review of Biomedical Engineering
(2017)
This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical image...
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Open Access
DOI: https://doi.org/10.1146/annurev-bioeng-071516-044442
PMC: 5479722