Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming

TA Shaikh, T Rasool, FR Lone - Computers and Electronics in Agriculture, 2022 - Elsevier
The digitalization of data has resulted in a data tsunami in practically every industry of data-
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …

Technological revolutions in smart farming: Current trends, challenges & future directions

V Sharma, AK Tripathi, H Mittal - Computers and Electronics in Agriculture, 2022 - Elsevier
With increasing population, the demand for agricultural productivity is rising to meet the goal
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …

[HTML][HTML] Advances in agriculture robotics: A state-of-the-art review and challenges ahead

LFP Oliveira, AP Moreira, MF Silva - Robotics, 2021 - mdpi.com
The constant advances in agricultural robotics aim to overcome the challenges imposed by
population growth, accelerated urbanization, high competitiveness of high-quality products …

[HTML][HTML] A review of robots, perception, and tasks in precision agriculture

A Botta, P Cavallone, L Baglieri, G Colucci… - applied …, 2022 - mdpi.com
This review reports the recent state of the art in the field of mobile robots applied to precision
agriculture. After a brief introduction to precision agriculture, the review focuses on two main …

[HTML][HTML] Agricultural robotics for field operations

S Fountas, N Mylonas, I Malounas, E Rodias… - Sensors, 2020 - mdpi.com
Modern agriculture is related to a revolution that occurred in a large group of technologies
(eg, informatics, sensors, navigation) within the last decades. In crop production systems …

Machine learning for smart agriculture and precision farming: towards making the fields talk

TA Shaikh, WA Mir, T Rasool, S Sofi - Archives of Computational Methods …, 2022 - Springer
In almost every sector, data-driven business, the digitization of the data has generated a
data tsunami. In addition, man-to-machine digital data handling has magnified the …

Tomato plant disease classification using multilevel feature fusion with adaptive channel spatial and pixel attention mechanism

CK Sunil, CD Jaidhar, N Patil - Expert Systems with Applications, 2023 - Elsevier
Agriculture's productivity has decreased in the last decade due to climate change and
inappropriate usage of water, fertilizer, and pesticides, which stimulate plant diseases. Plant …

A deep learning-based approach for banana leaf diseases classification

J Amara, B Bouaziz, A Algergawy - Datenbanksysteme für Business …, 2017 - dl.gi.de
Plant diseases are important factors as they result in serious reduction in quality and
quantity of agriculture products. Therefore, early detection and diagnosis of these diseases …

Vine disease detection in UAV multispectral images using optimized image registration and deep learning segmentation approach

M Kerkech, A Hafiane, R Canals - Computers and Electronics in Agriculture, 2020 - Elsevier
One of the major goals of tomorrow's agriculture is to increase agricultural productivity but
above all the quality of production while significantly reducing the use of inputs. Meeting this …

Agricultural robots for field operations: Concepts and components

A Bechar, C Vigneault - Biosystems engineering, 2016 - Elsevier
This review investigates the research effort, developments and innovation in agricultural
robots for field operations, and the associated concepts, principles, limitations and gaps …