A review of the challenges of using deep learning algorithms to support decision-making in agricultural activities

K Alibabaei, PD Gaspar, TM Lima, RM Campos… - Remote Sensing, 2022 - mdpi.com
Deep Learning has been successfully applied to image recognition, speech recognition, and
natural language processing in recent years. Therefore, there has been an incentive to …

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 …

Automatic bunch detection in white grape varieties using YOLOv3, YOLOv4, and YOLOv5 deep learning algorithms

M Sozzi, S Cantalamessa, A Cogato, A Kayad… - Agronomy, 2022 - mdpi.com
Over the last few years, several Convolutional Neural Networks for object detection have
been proposed, characterised by different accuracy and speed. In viticulture, yield …

A performance analysis of a litchi picking robot system for actively removing obstructions, using an artificial intelligence algorithm

C Wang, C Li, Q Han, F Wu, X Zou - Agronomy, 2023 - mdpi.com
Litchi is a highly favored fruit with high economic value. Mechanical automation of litchi
picking is a key link for improving the quality and efficiency of litchi harvesting. Our research …

[HTML][HTML] Simultaneous fruit detection and size estimation using multitask deep neural networks

M Ferrer-Ferrer, J Ruiz-Hidalgo, E Gregorio… - Biosystems …, 2023 - Elsevier
The measurement of fruit size is of great interest to estimate the yield and predict the harvest
resources in advance. This work proposes a novel technique for in-field apple detection and …

Swin-Transformer-YOLOv5 for real-time wine grape bunch detection

S Lu, X Liu, Z He, X Zhang, W Liu, M Karkee - Remote Sensing, 2022 - mdpi.com
Precise canopy management is critical in vineyards for premium wine production because
maximum crop load does not guarantee the best economic return for wine producers. The …

Advanced technology in agriculture industry by implementing image annotation technique and deep learning approach: A review

N Mamat, MF Othman, R Abdoulghafor, SB Belhaouari… - Agriculture, 2022 - mdpi.com
The implementation of intelligent technology in agriculture is seriously investigated as a way
to increase agriculture production while reducing the amount of human labor. In agriculture …

Identification and classification of mechanical damage during continuous harvesting of root crops using computer vision methods

A Osipov, V Shumaev, A Ekielski, T Gataullin… - IEEE …, 2022 - ieeexplore.ieee.org
Detecting sugar beetroot crops with mechanical damage using machine learning methods is
necessary for fine-tuning beet harvester units. The Agrifac HEXX TRAXX harvester with an …

Retrieving soil moisture from grape growing areas using multi-feature and stacking-based ensemble learning modeling

S Tao, X Zhang, R Feng, W Qi, Y Wang… - … and Electronics in …, 2023 - Elsevier
Soil moisture (SM) is an essential parameter for crop growth and development, and temporal
and spatial variation in SM in agricultural fields varies by crop type due to corresponding …

[HTML][HTML] Deep learning YOLO-based solution for grape bunch detection and assessment of biophysical lesions

I Pinheiro, G Moreira, D Queirós da Silva, S Magalhães… - Agronomy, 2023 - mdpi.com
The world wine sector is a multi-billion dollar industry with a wide range of economic
activities. Therefore, it becomes crucial to monitor the grapevine because it allows a more …