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Analysis and Classification of Word Co-Occurrence Networks From Alzheimer’s Patients and Controls

Tristan Millington, Saturnino Luz • Frontiers in Computer Science (2021)

In this paper we construct word co-occurrence networks from transcript data of controls and patients with potential Alzheimer’s disease using the ADReSS challenge dataset of spontaneous speech. We examine measures of the structure of these ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomp.2021.649508

Natural Language Processing in Oncology

Wen-wai Yim, Meliha Yetişgen, William Proctor Harris, Sharon W. Kwan • JAMA Oncology (2016)

IMPORTANCE: Natural language processing (NLP) has the potential to accelerate translation of cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of personalized medicine. This technology can harvest im...

OPENALEX DOI: https://doi.org/10.1001/jamaoncol.2016.0213

Deep Neural Networks and Kernel Density Estimation for Detecting Human Activity Patterns from Geo-Tagged Images: A Case Study of Birdwatching on Flickr

Caglar Koylu, Chang Zhao, Wei Shao • ISPRS International Journal of Geo-Information (2019)

Thanks to recent advances in high-performance computing and deep learning, computer vision algorithms coupled with spatial analysis methods provide a unique opportunity for extracting human activity patterns from geo-tagged social media ima...

DOAJ Open Access (DOAJ) DOI: 10.3390/ijgi8010045

Vision-Based Autonomous Landing of a Quadrotor on the Perturbed Deck of an Unmanned Surface Vehicle

Riccardo Polvara, Sanjay Sharma, Jian Wan, Andrew Manning et al. • Drones (2018)

Autonomous landing on the deck of an unmanned surface vehicle (USV) is still a major challenge for unmanned aerial vehicles (UAVs). In this paper, a fiducial marker is located on the platform so as to facilitate the task since it is possibl...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones2020015

Human Behavior Analysis: A Comprehensive Survey on Techniques, Applications, Challenges, and Future Directions

Siham Essahraui, Ismail Lamaakal, Yassine Maleh, Khalid El Makkaoui et al. • IEEE Access (2025)

Human Behavior Analysis (HBA) has emerged as a critical interdisciplinary field, combining psychology, sociology, artificial intelligence, and data science to model, understand, and predict human behavior across diverse domains. This paper ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3589938

Computer vision applications in vascular surgery: From preoperative mapping to intraoperative flow assessment

Daniela Arbeláez-Lelion, Francisco Ocaziones, Mateo José Murcia-Ramos, Samuel Salgado et al. • Cirugía Cardiovascular (2026)

Artificial intelligence (AI) and computer vision (CV) are increasingly applied in vascular surgery for preoperative mapping and intraoperative flow/perfusion assessment, with potential to enhance safety and efficiency. However, the extent o...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.circv.2025.10.002

Strawberry plant wetness detection using computer vision and deep learning

Arth Patel, Won Suk Lee, Natalia A. Peres, Clyde W. Fraisse • Smart Agricultural Technology (2021)

Botrytis fruit rot and anthracnose are fungal diseases of strawberry. These diseases are a significant contributor to yield losses, requiring farmers to use fungicides frequently to prevent them. The proliferation of botrytis and anthracnos...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.atech.2021.100013

Research on Landscape Perception and Visual Attributes Based on Social Media Data—A Case Study on Wuhan University

Xia Zhang, Danning Xu, Ni Zhang • Applied Sciences (2022)

With the rapid rise of social media, the photo-taking behavior of tourists and their uploaded photos provide a new perspective to explore landscape visual characters. In this study, we provide methodological advancements for assessing lands...

DOAJ Open Access (DOAJ) DOI: 10.3390/app12168346

Computer vision uncovers predictors of physical urban change

Nikhil Naik, Scott Duke Kominers, Ramesh Raskar, Edward L. Glaeser et al. • Proceedings of the National Academy of Sciences (2017)

Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the phys...

OPENALEX Open Access DOI: https://doi.org/10.1073/pnas.1619003114 PMC: 5530649

Automated detection of bicycle helmets using deep learning

Felix Wilhelm Siebert, Christoffer Riis, Kira Hyldekær Janstrup, Hanhe Lin et al. • Journal of Cycling and Micromobility Research (2024)

Bicycle helmets are a main measure for injury prevention in case of a crash and are a central variable in transport safety studies. Despite this, helmet use data is only collected sporadically, as the observation of helmet use in traffic by...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jcmr.2024.100013

Turning Features Detection from Aerial Images: Model Development and Application on Florida’s Public Roadways

Richard Boadu Antwi, Michael Kimollo, Samuel Yaw Takyi, Eren Erman Ozguven et al. • Smart Cities (2024)

Advancements in computer vision are rapidly revolutionizing the way traffic agencies gather roadway geometry data, leading to significant savings in both time and money. Utilizing aerial and satellite imagery for data collection proves to b...

DOAJ Open Access (DOAJ) DOI: 10.3390/smartcities7030059

SFCN: Symmetric feature comparison network for detecting ischemic stroke lesions on CT images

Long Zhang, Chuang Zhu, YueWei Wu, Yang Yang et al. • IET Image Processing (2021)

Abstract Ischemic stroke is the most common stroke and the leading cause of disability and death in the world. Computed tomography (CT) is a popular and economical diagnostic device for the stroke, However the ischemic stroke lesions are no...

DOAJ Open Access (DOAJ) DOI: 10.1049/ipr2.12267

Attention mechanisms in computer vision: A survey

Meng-Hao Guo, Tian-Xing Xu, Jiangjiang Liu, Zheng-Ning Liu et al. • Computational Visual Media (2022)

Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s41095-022-0271-y

Euclid Quick Data Release (Q1)

Bazzanini L., Angora G., Bergamini P., Meneghetti M. et al. • Astronomy & Astrophysics (2026)

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust a...

DOAJ Open Access (DOAJ) DOI: 10.1051/0004-6361/202557590

Computer Vision Metrics

Scott Krig • Apress eBooks (2014)

Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necess...

OPENALEX Open Access DOI: https://doi.org/10.1007/978-1-4302-5930-5

Evaluating the ergonomic deficiencies in computer workstations and investigating their correlation with reported musculoskeletal disorders and visual symptoms among computer users in Bangladeshi university

Md Golam Kibria, Md Shohel Parvez, Palash Saha, Subrata Talapatra • Heliyon (2023)

Background: Nowadays, computer users are facing musculoskeletal disorders (MSDs) and visual symptoms. Prolonged sitting in inappropriate, awkward, and static postures on the computer workstation may cause musculoskeletal disorders (MSDs). S...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.heliyon.2023.e22179

Assimilation of ASCAT Radar Backscatter Coefficients over Southwestern France

Timothée Corchia, Bertrand Bonan, Nemesio Rodríguez-Fernández, Gabriel Colas et al. • Remote Sensing (2023)

In this work, Advanced SCATterometer (ASCAT) backscatter data are directly assimilated into the interactions between soil, biosphere, and atmosphere (ISBA) land surface model using Meteo-France’s global Land Data Assimilation System (LDAS-M...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs15174258