Transforming weed management in sustainable agriculture with artificial intelligence: A systematic literature review towards weed identification and deep learning

M Vasileiou, LS Kyriakos, C Kleisiari, G Kleftodimos… - Crop Protection, 2023 - Elsevier
In the face of increasing agricultural demands and environmental concerns, the effective
management of weeds presents a pressing challenge in modern agriculture. Weeds not only …

[HTML][HTML] Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

H Tao, S Xu, Y Tian, Z Li, Y Ge, J Zhang, Y Wang… - Plant …, 2022 - cell.com
Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of
genomics and environment on plants, limiting the progress of smart breeding and precise …

[HTML][HTML] A cloud enabled crop recommendation platform for machine learning-driven precision farming

NN Thilakarathne, MSA Bakar, PE Abas, H Yassin - Sensors, 2022 - mdpi.com
Modern agriculture incorporated a portfolio of technologies to meet the current demand for
agricultural food production, in terms of both quality and quantity. In this technology-driven …

Semi-supervised learning and attention mechanism for weed detection in wheat

T Liu, X Jin, L Zhang, J Wang, Y Chen, C Hu, J Yu - Crop Protection, 2023 - Elsevier
Abstract Machine vision-based precision herbicide application in wheat (Triticum aestivum
L.) can substantially reduce herbicide input. However, detecting newly emerged weeds in …

A novel transfer deep learning method for detection and classification of plant leaf disease

P Kaur, S Harnal, V Gautam, MP Singh… - Journal of Ambient …, 2023 - Springer
The major cause of plant mortality and devastation, particularly among trees is plant
diseases. This problem, however, may be handled and treated effectively through early …

Crop phenotyping in a context of global change: What to measure and how to do it

JL Araus, SC Kefauver, O Vergara‐Díaz… - Journal of Integrative …, 2022 - Wiley Online Library
High‐throughput crop phenotyping, particularly under field conditions, is nowadays
perceived as a key factor limiting crop genetic advance. Phenotyping not only facilitates …

[PDF][PDF] A Deep Learning-Based Novel Approach for Weed Growth Estimation.

AM Mishra, S Harnal, K Mohiuddin… - … Automation & Soft …, 2022 - researchgate.net
Automation of agricultural food production is growing in popularity in scientific communities
and industry. The main goal of automation is to identify and detect weeds in the crop. Weed …

[HTML][HTML] Machine learning for plant stress modeling: A perspective towards hormesis management

AK Rico-Chávez, JA Franco, AA Fernandez-Jaramillo… - Plants, 2022 - mdpi.com
Plant stress is one of the most significant factors affecting plant fitness and, consequently,
food production. However, plant stress may also be profitable since it behaves hormetically; …

[HTML][HTML] Continual deep learning for time series modeling

SI Ao, H Fayek - Sensors, 2023 - mdpi.com
The multi-layer structures of Deep Learning facilitate the processing of higher-level
abstractions from data, thus leading to improved generalization and widespread …

[HTML][HTML] Generative adversarial networks for biomedical time series forecasting and imputation

S Festag, J Denzler, C Spreckelsen - Journal of Biomedical Informatics, 2022 - Elsevier
In the present systematic review we identified and summarised current research activities in
the field of time series forecasting and imputation with the help of generative adversarial …