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Computer vision methods and algorithms for automatic detection and classification of objects in decision support systems in agriculture

Yablokova Alena, Kovalev Igor, Kovalev Dmitry, Podoplelova Valeria et al. • E3S Web of Conferences (2024)

The paper examines aspects of developing and formalizing the task of applying computer vision methods and algorithms using OpenCV (implemented in Python version 3.13 notation) for automatic detection and classification of objects in decisio...

DOAJ Open Access (DOAJ) DOI: 10.1051/e3sconf/202454803023

DIAGNOSTICS OF RUSTS AND SPOTTS OF WHEAT USING COMPUTER VISION METHODS

Irina V. Arinicheva, Igor V. Arinichev, Galina V. Volkova, Sergey V. Polyanskikh • Siberian Journal of Life Sciences and Agriculture (2022)

Purpose. To investigate the possibility of diagnosing yellow and brown rust (Puccinia striiformis f. sp. tritici West. Puccinia triticina f. sp. tritici Erikss), yellow spot (Pyrenophora tritici-repentis (Died.) Drechsler) on wheat leaves f...

DOAJ Open Access (DOAJ) DOI: 10.12731/2658-6649-2022-14-1-248-261

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Rittik Chandra Das Turjy, Fahmid Al Farid, Fahmid Al Farid, Md. Hasan Imam Bijoy et al. • Frontiers in Artificial Intelligence (2026)

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1884567

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

Deep learning based computer vision approaches for smart agricultural applications

V. G. Dhanya, Anakkallan Subeesh, Nand Lal Kushwaha, Dinesh Kumar Vishwakarma et al. • Artificial Intelligence in Agriculture (2022)

The agriculture industry is undergoing a rapid digital transformation and is growing powerful by the pillars of cutting-edge approaches like artificial intelligence and allied technologies. At the core of artificial intelligence, deep learn...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.aiia.2022.09.007

VISION-LINK AI Smart Glass: An Edge-Cloud Wearable AI System for Workflow Automation and Digital Inclusion in Emerging Economies

Buhari Salisu • International Journal of AI and Advanced Computing (2026)

The rapid advancement of Artificial Intelligence (AI), wearable computing, and Internet of Things (IoT) technologies has significantly transformed digital interactions across various sectors. However, the adoption of smart wearable technolo...

DOAJ Open Access (DOAJ) DOI: 10.5281/zenodo.21981139

Autonomous Robotic Platform for Precision Viticulture: Integrated Mobility, Multimodal Sensing, and AI-Based Leaf Sampling

Miriana Russo, Corrado Santoro, Federico Fausto Santoro, Alessio Tudisco • Actuators (2026)

Viticulture is facing growing economic and environmental pressures that demand a transition toward intelligent and autonomous crop management systems. Phytopathologies remain one of the most critical threats, causing substantial yield losse...

DOAJ Open Access (DOAJ) DOI: 10.3390/act15020091

A survey of public datasets for computer vision tasks in precision agriculture

Yuzhen Lu, Sierra N. Young • Computers and Electronics in Agriculture (2020)

Computer vision technologies have attracted significant interest in precision agriculture in recent years. At the core of robotics and artificial intelligence, computer vision enables various tasks from planting to harvesting in the crop pr...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.compag.2020.105760

Fruits and vegetables quality evaluation using computer vision: A review

Anuja Bhargava, Atul Bansal • Journal of King Saud University - Computer and Information Sciences (2018)

In agriculture science, automation increases the quality, economic growth and productivity of the country. The export market and quality evaluation are affected by assorting of fruits and vegetables. The crucial sensory characteristic of fr...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.jksuci.2018.06.002

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

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

Monitoring the spread of a pathogenic insect on vineyards using UAS

V. Longhi, A. Martino, A. M. Lingua, P. F. Maschio et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2024)

Globalisation has contributed to rapid economic growth but has also exposed vulnerabilities such as the spread of pests in agriculture. An example is the Popillia Japonica Newman beetle, introduced to Italy in 2014, which has caused signifi...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLVIII-1-2024-443-2024

Tamarind health assessment dataset: Images of shelled, unshelled, and mixed tamarind podsMendeley Data

Amol Bhosle, Deepali Godse, Sandip Thite, Kailas Patil et al. • Data in Brief (2025)

This data paper provides image dataset that includes 8432 high-quality images of Tamarindus indica [1] (tamarind), categorized into six types: Shelled Healthy Single, Shelled Healthy Multiple, Unshelled Healthy Single, Unshelled Healthy Mul...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2025.111917

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

Resting Posture Recognition Method for Suckling Piglets Based on Piglet Posture Recognition (PPR)–You Only Look Once

Jinxin Chen, Luo Liu, Peng Li, Wen Yao et al. • Agriculture (2025)

The resting postures of piglets are crucial indicators for assessing their health status and environmental comfort. This study proposes a resting posture recognition method for piglets during lactation based on the PPR-YOLO model, aiming to...

DOAJ Open Access (DOAJ) DOI: 10.3390/agriculture15030230