Automation in agriculture by machine and deep learning techniques: A review of recent developments

MH Saleem, J Potgieter, KM Arif - Precision Agriculture, 2021 - Springer
Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …

[HTML][HTML] Computer vision technology in agricultural automation—A review

H Tian, T Wang, Y Liu, X Qiao, Y Li - Information Processing in Agriculture, 2020 - Elsevier
Computer vision is a field that involves making a machine “see”. This technology uses a
camera and computer instead of the human eye to identify, track and measure targets for …

Detection of Camellia oleifera Fruit in Complex Scenes by Using YOLOv7 and Data Augmentation

D Wu, S Jiang, E Zhao, Y Liu, H Zhu, W Wang… - Applied sciences, 2022 - mdpi.com
Rapid and accurate detection of Camellia oleifera fruit is beneficial to improve the picking
efficiency. However, detection faces new challenges because of the complex field …

Faster R-CNN for multi-class fruit detection using a robotic vision system

S Wan, S Goudos - Computer Networks, 2020 - Elsevier
An accurate and real-time image based multi-class fruit detection system is important for
facilitating higher level smart farm tasks such as yield map** and robotic harvesting …

Development of a sweet pepper harvesting robot

B Arad, J Balendonck, R Barth… - Journal of Field …, 2020 - Wiley Online Library
This paper presents the development, testing and validation of SWEEPER, a robot for
harvesting sweet pepper fruit in greenhouses. The robotic system includes a six degrees of …

[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 …

A review on the combination of deep learning techniques with proximal hyperspectral images in agriculture

JGA Barbedo - Computers and Electronics in Agriculture, 2023 - Elsevier
Hyperspectral images can capture the spectral characteristics of surfaces and objects,
providing a 2-D spacial component to the spectral profiles found in a given scene. There are …

A deep residual neural network identification method for uneven dust accumulation on photovoltaic (PV) panels

S Fan, Y Wang, S Cao, B Zhao, T Sun, P Liu - Energy, 2022 - Elsevier
Uneven dust accumulation can significantly influence the thermal balance between different
regions of photovoltaic (PV) panels, leading to a sharp decrease in power generation …

Recognition of bloom/yield in crop images using deep learning models for smart agriculture: A review

B Darwin, P Dharmaraj, S Prince, DE Popescu… - Agronomy, 2021 - mdpi.com
Precision agriculture is a crucial way to achieve greater yields by utilizing the natural
deposits in a diverse environment. The yield of a crop may vary from year to year depending …

Real-time 3D printing remote defect detection (stringing) with computer vision and artificial intelligence

K Paraskevoudis, P Karayannis, EP Koumoulos - Processes, 2020 - mdpi.com
This work describes a novel methodology for the quality assessment of a Fused Filament
Fabrication (FFF) 3D printing object during the printing process through AI-based Computer …