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 …

Review on convolutional neural network (CNN) applied to plant leaf disease classification

J Lu, L Tan, H Jiang - Agriculture, 2021 - mdpi.com
Crop production can be greatly reduced due to various diseases, which seriously endangers
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …

Machine learning applications for precision agriculture: A comprehensive review

A Sharma, A Jain, P Gupta, V Chowdary - IEEE Access, 2020 - ieeexplore.ieee.org
Agriculture plays a vital role in the economic growth of any country. With the increase of
population, frequent changes in climatic conditions and limited resources, it becomes a …

Identification of plant-leaf diseases using CNN and transfer-learning approach

SM Hassan, AK Maji, M Jasiński, Z Leonowicz… - Electronics, 2021 - mdpi.com
The timely identification and early prevention of crop diseases are essential for improving
production. In this paper, deep convolutional-neural-network (CNN) models are …

Agricultural plant diseases identification: From traditional approach to deep learning

J Kotwal, R Kashyap, S Pathan - Materials Today: Proceedings, 2023 - Elsevier
Plant disease computerization in agriculture areas an important for every country, as the
population rate increases the demand for food supply also increases. Today, the significant …

A survey of deep convolutional neural networks applied for prediction of plant leaf diseases

VS Dhaka, SV Meena, G Rani, D Sinwar, MF Ijaz… - Sensors, 2021 - mdpi.com
In the modern era, deep learning techniques have emerged as powerful tools in image
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …

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 …

A review of deep learning techniques used in agriculture

I Attri, LK Awasthi, TP Sharma, P Rathee - Ecological Informatics, 2023 - Elsevier
Deep learning (DL) is a robust data-analysis and image-processing technique that has
shown great promise in the agricultural sector. In this study, 129 papers that are based on …

Plant disease detection and classification by deep learning

MH Saleem, J Potgieter, KM Arif - Plants, 2019 - mdpi.com
Plant diseases affect the growth of their respective species, therefore their early identification
is very important. Many Machine Learning (ML) models have been employed for the …

Remote sensing in agriculture—accomplishments, limitations, and opportunities

S Khanal, K Kc, JP Fulton, S Shearer, E Ozkan - Remote Sensing, 2020 - mdpi.com
Remote sensing (RS) technologies provide a diagnostic tool that can serve as an early
warning system, allowing the agricultural community to intervene early on to counter …