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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

Florence: A New Foundation Model for Computer Vision

Lu Yuan, Dongdong Chen, Yi‐Ling Chen, Noel Codella et al. • arXiv (Cornell University) (2021)

Automated visual understanding of our diverse and open world demands computer vision models to generalize well with minimal customization for specific tasks, similar to human vision. Computer vision foundation models, which are trained on d...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.2111.11432

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

Edge AI for Industrial Visual Inspection: YOLOv8-Based Visual Conformity Detection Using Raspberry Pi

Marcelo T. Okano, William Aparecido Celestino Lopes, Sergio Miele Ruggero, Oduvaldo Vendrametto et al. • Algorithms (2025)

This paper presents a lightweight and cost-effective computer vision solution for automated industrial inspection using You Only Look Once (YOLO) v8 models deployed on embedded systems. The YOLOv8 Nano model, trained for 200 epochs, achieve...

DOAJ Open Access (DOAJ) DOI: 10.3390/a18080510

An Implementation of an optimized dual-axis solar tracking algorithm for concentrating solar power plants deployment

Eric Tutu Tchao, Simon Atuah Asakipaam, Yesuenyeagbe Atsu Kwabla Fiagbe, Bright Yeboah-Akowuah et al. • Scientific African (2022)

A recent assessment of a pilot concentrating solar power plant in Ghana noticed the failure of the tracking system to accurately align the multifaceted heliostats toward the sun and focus the sunbeams onto the target. A further review of so...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.sciaf.2022.e01228

Scale Accuracy Evaluation of Image-Based 3D Reconstruction Strategies Using Laser Photogrammetry

Klemen Istenič, Nuno Gracias, Aurélien Arnaubec, Javier Escartín et al. • Remote Sensing (2019)

Rapid developments in the field of underwater photogrammetry have given scientists the ability to produce accurate 3-dimensional (3D) models which are now increasingly used in the representation and study of local areas of interest. This pa...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs11182093

OmniVO: Toward Robust Omni Directional Visual Odometry With Multicamera Collaboration for Challenging Conditions

Zeeshan Javed, Gon-Woo Kim • IEEE Access (2022)

With the recent developments in computer vision, vision-based odometry plays an increasingly important role in the field of autonomous systems. However, using traditional visual odometry or simultaneous localization and mapping (vSLAM) only...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2022.3204870

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

A COMPARATIVE STUDY ON REINFORCEMENT LEARNING BASED VISUAL DIALOG SYSTEMS

Mostafa Aref, Ghada Elshamy, Marco Alfonse, Islam Hegazy • International Journal of Intelligent Computing and Information Sciences (2024)

Recently the conjunction between vision and language has created many intersecting tasks as visual question-answering systems, image captioning, etc. Specifically, dialog systems that depend on a visual scene play an important role in impro...

DOAJ Open Access (DOAJ) DOI: 10.21608/ijicis.2024.295310.1339

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 lightweight fully convolutional neural network for efficient and accurate tunnel crack detection

Hao Huang, G.T.S. Ho, V. Tang, E.W.H. Chow et al. • Journal of Advanced Research (2026)

Introduction: Crack damage is a significant issue in tunnel environments, requiring efficient and reliable detection to ensure structural integrity. Many existing solutions are computationally expensive, making them unsuitable for the tight...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jare.2025.11.052