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Design and Implementation of a Ball-Plate Control System and Python Script for Educational Purposes in STEM Technologies

Vladimir Tudić, Damir Kralj, Josip Hoster, Tomislav Tropčić • Sensors (2022)

This paper presents the process of designing, fabricating, assembling, programming and optimizing a prototype nonlinear mechatronic Ball-Plate System (BPS) as a laboratory platform for engineering education STEM. Due to the nonlinearity and...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22051875

Estimating Black Oat Biomass Using Digital Surface Models and a Vegetation Index Derived from RGB-Based Aerial Images

Lucas Renato Trevisan, Lisiane Brichi, Tamara Maria Gomes, Fabrício Rossi • Remote Sensing (2023)

Responsible for food production and industry inputs, agriculture needs to adapt to worldwide increasing demands and environmental requirements. In this scenario, black oat has gained environmental and economic importance since it can be use...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs15051363

Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence

Muhammad Salihin Saealal, Mohd Zamri Ibrahim, David. J. Mulvaney, Mohd Ibrahim Shapiai et al. • PLoS ONE (2022)

Deep learning is notably successful in data analysis, computer vision, and human control. Nevertheless, this approach has inevitably allowed the development of DeepFake video sequences and images that could be altered so that the changes ar...

DOAJ Open Access (DOAJ)

Lipid vesicle shape analysis from populations using light video microscopy and computer vision.

Jernej Zupanc, Barbara Drašler, Sabina Boljte, Veronika Kralj-Iglič et al. • PLoS ONE (2014)

We present a method for giant lipid vesicle shape analysis that combines manually guided large-scale video microscopy and computer vision algorithms to enable analyzing vesicle populations. The method retains the benefits of light microscop...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0113405

Fruit freshness detection based on multi-task convolutional neural network

Yinsheng Zhang, Xudong Yang, Yongbo Cheng, Xiaojun Wu et al. • Current Research in Food Science (2024)

Background: Fruit freshness detection by computer vision is essential for many agricultural applications, e.g., automatic harvesting and supply chain monitoring. This paper proposes to use the multi-task learning (MTL) paradigm to build a d...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.crfs.2024.100733

Computer Vision and Natural Constraints

C. M. Brown • Science (1984)

Computer vision, the automatic construction of scene descriptions from image input data, has just entered its second decade. Approaches have varied widely, especially in the amounts of symbolic, domain-dependent knowledge and inference that...

OPENALEX DOI: https://doi.org/10.1126/science.224.4655.1299

Computer vision vs. human vision

Bo Zhang • IEEE International Conference on Cognitive Informatics (2010)

In object recognition (classification), it was known that the human brain processes visual information in semantic space mainly, that is, extracting the semantically meaningful features such as line-segments, boundaries, shape and so on. Bu...

OPENALEX DOI: https://doi.org/10.1109/coginf.2010.5599750

Federated Learning in Computer Vision

Donald Shenaj, Giulia Rizzoli, Pietro Zanuttigh • IEEE Access (2023)

Federated Learning (FL) has recently emerged as a novel machine learning paradigm allowing to preserve privacy and to account for the distributed nature of the learning process in many real-world settings. Computer vision tasks deal with hu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1109/access.2023.3310400

Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

Hyungchul Yoon, Vedhus Hoskere, Jong-Woong Park, Billie F. Spencer • Sensors (2017)

Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a st...

DOAJ Open Access (DOAJ) DOI: 10.3390/s17092075

Performance Benchmarking: Pre-trained Models and Custom Convolutional Neural Networks in Deep Learning

Sheemona Joseph C., S. Ganesh, S. Kannadhasan, K. Selvipriya • Journal of Informatics and Web Engineering (2025)

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial ta...

DOAJ Open Access (DOAJ) DOI: 10.33093/jiwe.2025.4.2.14

Improved U-Net Model for Road Crack Detection Based on Residual and Attention Mechanism

YU Haiyang, JING Peng, ZHANG Wentao, XIE Saifei, HUA Zhihua, SONG Caoyuan • Jisuanji gongcheng (2023)

Road cracks are an important part of road safety detection,and with the development of deep learning and computer vision,methods for extracting crack information in road images using deep learning methods are maturing.Existing deep learning...

DOAJ Open Access (DOAJ) DOI: 10.19678/j.issn.1000-3428.0064952

A Complete System for Automated Semantic–Geometric Mapping of Corrosion in Industrial Environments

Rui Pimentel de Figueiredo, Stefan Nordborg Eriksen, Ignacio Rodriguez, Simon Bøgh • Automation (2025)

Corrosion, a naturally occurring process leading to the deterioration of metallic materials, demands diligent detection for quality control and the preservation of metal-based objects, especially within industrial contexts. Traditional tech...

DOAJ Open Access (DOAJ) DOI: 10.3390/automation6020023

Lightweight Road Image Segmentation Algorithm Based on Multi-Scale Feature Fusion for Blind Guiding Scenarios

SHA Yuyang, LU Jingtao, DU Haofan, ZHAI Xiaobing, MENG Weiyu, LIAN Xu, LUO Gang, LI Kefeng • Jisuanji gongcheng (2025)

Image segmentation is a crucial technology for environmental perception, and it is widely used in various scenarios such as autonomous driving and virtual reality. With the rapid development of technology, computer vision-based blind guidin...

DOAJ Open Access (DOAJ) DOI: 10.19678/j.issn.1000-3428.0068674

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access (2019)

Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2932037

Computer Vision Tools for 3D Modelling in Archaeology

Mauro Lo Brutto, Paola Meli • International Journal of Heritage in the Digital Era (2012)

In archaeological Cultural Heritage study 3D modelling has become a very useful process to obtain indispensable data for documentation and visualization. Nowadays the continuous request to achieve photorealistic 3D models has led to testing...

OPENALEX Open Access DOI: https://doi.org/10.1260/2047-4970.1.0.1