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Convolutional-de-convolutional neural networks for recognition of surgical workflow

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

Unmanned Aerial Vehicle-Based Structural Health Monitoring and Computer Vision-Aided Procedure for Seismic Safety Measures of Linear Infrastructures

Luna Ngeljaratan, Elif Ecem Bas, Mohamed A. Moustafa • Sensors (2024)

Computer vision in the structural health monitoring (SHM) field has become popular, especially for processing unmanned aerial vehicle (UAV) data, but still has limitations both in experimental testing and in practical applications. Prior wo...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24051450

MAT-Fly: An Educational Platform for Simulating Unmanned Aerial Vehicles Aimed to Detect and Track Moving Objects

Giuseppe Silano, Luigi Iannelli • IEEE Access (2021)

The main motivation of this work is to propose a simulation approach for a specific task within the Unmanned Aerial Vehicle (UAV) field, i.e., the visual detection and tracking of arbitrary moving objects. In particular, it is described MAT...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3064758

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Ling-Yu Duan, Wen Gao, Yonghong Tian, Yuanning Li et al. • EURASIP Journal on Image and Video Processing (2010)

Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL) methods have shown great advantages in visual concept learning. As a visual concep...

DOAJ Open Access (DOAJ) DOI: 10.1155/2010/461450

Deep Learning for Understanding Satellite Imagery: An Experimental Survey

Sharada Prasanna Mohanty, Jakub Czakon, Kamil A. Kaczmarek, Kamil A. Kaczmarek et al. • Frontiers in Artificial Intelligence (2020)

Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in compu...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2020.534696

Monitoring pedestrian walking dynamics under environmental and policy influences in urban spaces

Mohamed A. Abdelwahab, Shizuo Kaji, Maiya Hori, Shigeru Takano • Computational Urban Science (2026)

Abstract Understanding how environmental conditions and policy interventions jointly shape pedestrian mobility is essential for designing resilient, adaptive, and human-centered urban spaces. This study presents a computer-vision framework ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43762-026-00284-3

Computer Vision and Pattern Recognition 2020

Zeynep Akata, Andreas Geiger, Torsten Sattler • International Journal of Computer Vision (2021)

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11263-021-01522-3

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

Deep learning based identification and tracking of railway bogie parts

Muhammad Zakir Shaikh, Zeeshan Ahmed, Enrique Nava Baro, Samreen Hussain et al. • Alexandria Engineering Journal (2024)

The Train Rolling-Stock Examination (TRSE) is a safety examination process that physically examines the bogie parts of a moving train, typically at speeds over 30 km/h. Currently, this inspection process is done manually by railway personne...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.aej.2024.07.064

The long non-coding RNA LINC00152 is essential for cell cycle progression through mitosis in HeLa cells

Linda Nötzold, Lukas Frank, Minakshi Gandhi, Maria Polycarpou-Schwarz et al. • Scientific Reports (2017)

Abstract In recent years, long non-coding RNA (lncRNA) research has identified essential roles of these transcripts in virtually all physiological cellular processes including tumorigenesis, but their functions and molecular mechanisms are ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-017-02357-0

The psychological impact of the Metaverse

Patrick Henz • Discover Psychology (2022)

Abstract The Metaverse is no revolution, but another step in the evolution of the internet. Today we can observe various 3D virtual worlds with different focuses and purposes, like meeting spaces, education, or classic gaming. Most of these...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44202-022-00061-3

A Survey of Deep Learning Techniques and Computer Vision in Robotic and Drone with Applications

Khazaal Abbas Maaroof Maysoon, Bouhlel Med Salim • BIO Web of Conferences (2024)

The methods of deep learning have lately demonstrated outstanding outcomes of robotic objects such as imagination, localization and striping. Its exceptional abilities in order to learn idealizations from complicated data gathered in the re...

DOAJ Open Access (DOAJ) DOI: 10.1051/bioconf/20249700008

Assessment of the possibility of machine learning for electronic equipment quality prediction

Anna S. Kolosova, Anna S. Kameneva, Georgii G. Chukov, Alexander Y. Nikiforov • Безопасность информационных технологий (2023)

The major algorithms and methods of machine learning are considered. A possibility of machine learning and neural network using for electronic equipment quality prediction is assessed. The paper provides examples of the successful applicati...

DOAJ Open Access (DOAJ) DOI: 10.26583/bit.2023.1.09

Applied research note: Predicting carcass portion weights for purebred turkey (Meleagris gallopavo) lines using a 2D imaging system

Shai Barbut, Emily M. Leishman, Ryley J. Vanderhout, Benjamin J. Wood et al. • Journal of Applied Poultry Research (2025)

Summary: Improving carcass portion yields (e.g., breast meat) is a major goal of modern turkey breeding and traditionally requires manual collection of portion weights. This can be a labor-intensive process considering the large amount of d...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.japr.2024.100506