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A Deep Learning-Driven Computer Vision and Web-Based Monitoring System for Automated Nutrient Management in Soilless Agriculture

Eda Nur Urtekin, Emre Dandıl • Journal of Agricultural Sciences (2026)

Sustainable food production increasingly relies on intelligent automation technologies that optimize resource usage while maintaining crop health. This study presents a deep learning-driven computer vision and web based monitoring system de...

DOAJ Open Access (DOAJ) DOI: 10.15832/ankutbd.1817471

The Validity and Reliability of the My Jump Lab App for the Measurement of Vertical Jump Performance Using Artificial Intelligence

Carlos Balsalobre-Fernández, Daniel Varela-Olalla • Sensors (2024)

The countermovement jump (CMJ) is a widely used test to assess lower body neuromuscular performance. This study aims to analyze the validity and reliability of an iOS application using artificial intelligence to measure CMJ height, force, v...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24247897

Evaluating Adversarial Robustness of No-Reference Image and Video Quality Assessment Models with Frequency-Masked Gradient Orthogonalization Adversarial Attack

Khaled Abud, Sergey Lavrushkin, Dmitry Vatolin • Big Data and Cognitive Computing (2025)

Neural-network-based models have made considerable progress in many computer vision areas over recent years. However, many works have exposed their vulnerability to malicious input data manipulation—that is, to adversarial attacks. Although...

DOAJ Open Access (DOAJ) DOI: 10.3390/bdcc9070166

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

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

Computer Perceptual Organization in Computer Vision

Sudeep Sarkar, Kim L. Boyer • Series in machine perception and artificial intelligence (1994)

This book describes the design of a complete, flexible system for perceptual organization in computer vision using graph theoretic techniques, voting methods, and an extension of the Bayesian networks called perceptual inference networks (P...

OPENALEX DOI: https://doi.org/10.1142/2421

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 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