From industry 4.0 to agriculture 4.0: Current status, enabling technologies, and research challenges

Y Liu, X Ma, L Shu, GP Hancke… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
The three previous industrial revolutions profoundly transformed agriculture industry from
indigenous farming to mechanized farming and recent precision agriculture. Industrial …

[HTML][HTML] Convolutional neural networks for image-based high-throughput plant phenoty**: a review

Y Jiang, C Li - Plant Phenomics, 2020 - spj.science.org
Plant phenoty** has been recognized as a bottleneck for improving the efficiency of
breeding programs, understanding plant-environment interactions, and managing …

Hybrid deep learning-based models for crop yield prediction

A Oikonomidis, C Catal, A Kassahun - Applied artificial intelligence, 2022 - Taylor & Francis
Predicting crop yield is a complex task since it depends on multiple factors. Although many
models have been developed so far in the literature, the performance of current models is …

Intelligent fruit yield estimation for orchards using deep learning based semantic segmentation techniques—a review

P Maheswari, P Raja, OE Apolo-Apolo… - Frontiers in plant …, 2021 - frontiersin.org
Smart farming employs intelligent systems for every domain of agriculture to obtain
sustainable economic growth with the available resources using advanced technologies …

[HTML][HTML] Fruit sizing using AI: a review of methods and challenges

JC Miranda, J Gené-Mola, M Zude-Sasse… - Postharvest Biology and …, 2023 - Elsevier
Fruit size at harvest is an economically important variable for high-quality table fruit
production in orchards and vineyards. In addition, knowing the number and size of the fruit …

Deep-learning-based counting methods, datasets, and applications in agriculture: A review

G Farjon, L Huijun, Y Edan - Precision Agriculture, 2023 - Springer
The number of objects is considered an important factor in a variety of tasks in the
agricultural domain. Automated counting can improve farmers' decisions regarding yield …

Computer vision and deep learning for precision viticulture

L Mohimont, F Alin, M Rondeau, N Gaveau… - Agronomy, 2022 - mdpi.com
During the last decades, researchers have developed novel computing methods to help
viticulturists solve their problems, primarily those linked to yield estimation of their crops …

Agi for agriculture

G Lu, S Li, G Mai, J Sun, D Zhu, L Chai, H Sun… - ar** in agriculture: A survey
AL Chandra, SV Desai, W Guo… - arxiv preprint arxiv …, 2020 - arxiv.org
In light of growing challenges in agriculture with ever growing food demand across the
world, efficient crop management techniques are necessary to increase crop yield. Precision …

[HTML][HTML] Weakly and semi-supervised detection, segmentation and tracking of table grapes with limited and noisy data

TA Ciarfuglia, IM Motoi, L Saraceni… - … and Electronics in …, 2023 - Elsevier
Detection, segmentation and tracking of fruits and vegetables are three fundamental tasks
for precision agriculture, enabling robotic harvesting and yield estimation applications …