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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

A Comprehensive Review on 3D Object Detection and 6D Pose Estimation With Deep Learning

Sabera Hoque, Md. Yasir Arafat, Shuxiang Xu, Ananda Maiti et al. • IEEE Access (2021)

Nowadays, computer vision with 3D (dimension) object detection and 6D (degree of freedom) pose assumptions are widely discussed and studied in the field. In the 3D object detection process, classifications are centered on the object’...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3114399

DEEP LEARNING-BASED DOOR AND WINDOW DETECTION FROM BUILDING FAÇADE

G. Sezen, M. Cakir, M. E. Atik, Z. Duran • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2022)

Detecting building façade elements is a crucial problem in computer vision for image interpretation. In Building Information Modeling (BIM) studies, the detection of building façade elements has an important role. BIM is a tool that allows ...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLIII-B4-2022-315-2022

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access (2020)

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3039858

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

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

A critical review on computer vision and artificial intelligence in food industry

Vijay Kakani, Van Huan Nguyen, Basivi Praveen Kumar, Hakil Kim et al. • Journal of Agriculture and Food Research (2020)

Emerging technologies such as computer vision and Artificial Intelligence (AI) are estimated to leverage the accessibility of big data for active training and yielding operational real time smart machines and predictable models. This phenom...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.jafr.2020.100033

Up-to-Date Scoping Review of Object Detection Methods for Macro Marine Debris

Zoe Moorton, Kamlesh Mistry, Rebecca Strachan, Shanfeng Hu • Journal of Marine Science and Engineering (2025)

Being able to accurately identify litter in a marine environment is crucial to cleaning up our seas and oceans. Research into object detection techniques to support this identification has been underway for over two decades. However, there ...

DOAJ Open Access (DOAJ) DOI: 10.3390/jmse13081590

Artificial Intelligence in Healthcare: Advancing Innovation and Ethics to Foster Well-Being

Bayram B., Leventi N., Vodenicharova A., Lamprianidou A. et al. • Acta Medica Bulgarica (2026)

Artificial intelligence (AI) is reshaping healthcare by enhancing diagnostic precision, treatment personalization, and overall patient care. By leveraging technologies such as machine learning, deep learning, natural language processing, an...

DOAJ Open Access (DOAJ) DOI: 10.2478/amb-2026-0050

From Data to Decisions: AI in Varicose Veins—Predicting, Diagnosing, and Guiding Effective Management

Lakshmi Sree Pugalenthi, Chris Garapati, Srivarshini Maddukuri, Fnu Kanwal et al. • Journal of Vascular Diseases (2025)

Background: Varicose veins (VVs) of the lower limbs, characterized by palpable, dilated, and tortuous veins, affect 2–73% of the global population. Artificial intelligence (AI) offers significant potential to enhance healthcare efficiency a...

DOAJ Open Access (DOAJ) DOI: 10.3390/jvd4020019

HawkEye: AI-Driven Software for Objective Analysis and Characterization of Nodular Cast Iron Microstructures

Javier Nieves, Antonio Serena-Barriuso, Guillermo Elejoste-Rementeria • Applied Sciences (2025)

Metallographic evaluation of nodular cast iron is crucial for quality control in the foundry industry. Traditionally, this process relies on experts who visually interpret microscopic images. This study introduces HawkEye, a comprehensive s...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15136991

A Self-Supervised One-Shot Learning Approach for Seismic Noise Reduction

Catarina de Nazaré Pereira Pinheiro, Roosevelt de Lima Sardinha, Pablo Machado Barros, André Bulcão et al. • Applied Sciences (2024)

Neural networks have been used in various computer vision applications, including noise removal. However, removing seismic noise via deep learning approaches faces a specific issue: the scarcity of labeled data. To address this difficulty, ...

DOAJ Open Access (DOAJ) DOI: 10.3390/app14219721