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Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection

Asim Niaz, Sareer Ul Amin, Shafiullah Soomro, Hamza Zia et al. • IEEE Access (2024)

Surveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods. This paper introduces an unsupervised end-t...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3435144

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

Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration

Francisco Troncoso-Pastoriza, Javier López-Gómez, Lara Febrero-Garrido • Sensors (2018)

This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporati...

DOAJ Open Access (DOAJ) DOI: 10.3390/s18072364

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

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

Evaluation of Modified FGSM-Based Data Augmentation Method for Convolutional Neural Network-Based Image Classification

Paulo Monteiro de Carvalho Monson, Vinicius Augusto Dare de Almeida, Gabriel Augusto David, Pedro Oliveira Conceição Junior et al. • Engineering Proceedings (2024)

Computer vision applications demand a significant amount of data for effective training and inference in many computer vision tasks. However, data insufficiency situations usually happen due to multiple reasons, resulting in computational m...

DOAJ Open Access (DOAJ) DOI: 10.3390/ecsa-11-20476

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

Enhanced Combined Techniques for Interval-Valued Intuitionistic Fuzzy Multiple-Attribute Group Decision-Making and Applications to Quality Evaluation of Large-Scale Multi-View 3D Reconstruction

Longpeng Bian, Chang Che • IEEE Access (2023)

With the widespread application of computer vision in many fields, quickly and accurately obtaining the three-dimensional information covered by the target object has become a concern in the field of vision research. Large scale multi view ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3327310

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

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

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