Machine learning in agriculture: A comprehensive updated review

L Benos, AC Tagarakis, G Dolias, R Berruto, D Kateris… - Sensors, 2021 - mdpi.com
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …

From smart farming towards unmanned farms: A new mode of agricultural production

T Wang, X Xu, C Wang, Z Li, D Li - Agriculture, 2021 - mdpi.com
Agriculture is the most important industry for human survival and solving the hunger problem
worldwide. With the growth of the global population, the demand for food is increasing …

Classification and yield prediction in smart agriculture system using IoT

A Gupta, P Nahar - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
The modern agriculture industry is data-centred, precise and smarter than ever. Advanced
development of Internet-of-Things (IoT) based systems redesigned “smart agriculture”. This …

Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks

MN Al-Andoli, SC Tan, WP Cheah - Information Sciences, 2022 - Elsevier
In this paper, a parallel deep learning-based community detection method in large complex
networks (CNs) is proposed. First, a CN partitioning method is employed to divide the CN …

A review on community detection in large complex networks from conventional to deep learning methods: A call for the use of parallel meta-heuristic algorithms

MN Al-Andoli, SC Tan, WP Cheah, SY Tan - IEEE Access, 2021 - ieeexplore.ieee.org
Complex networks (CNs) have gained much attention in recent years due to their
importance and popularity. The rapid growth in the size of CNs leads to more difficulties in …

[HTML][HTML] IOT-BASED professional crop recommendation system using a weight-based long-term memory approach

S Kiruthika, D Karthika - Measurement: Sensors, 2023 - Elsevier
For the vast majority of Indians, agriculture is their main source of income, and it plays a vital
role in the country's economy. The most prevalent issue Indian farmers have is that they do …

Crop yield forecasting by long short‐term memory network with Adam optimizer and Huber loss function in Andhra Pradesh, India

JR Dwaram, RK Madapuri - Concurrency and Computation …, 2022 - Wiley Online Library
In recent times, crop yield prediction gains more attention among researchers communities
to expand food production. In this article, an effort is done for crop yield prediction in Andhra …

[PDF][PDF] Optimized Deep Learning Methods for Crop Yield Prediction.

K Vignesh, A Askarunisa, AM Abirami - Comput. Syst. Sci. Eng., 2023 - cdn.techscience.cn
Crop yield has been predicted using environmental, land, water, and crop characteristics in
a prospective research design. When it comes to predicting crop production, there are a …

Quantile correlative deep feedforward multilayer perceptron for crop yield prediction

V Sivanantham, V Sangeetha, AA Alnuaim… - Computers & Electrical …, 2022 - Elsevier
Crop yield prediction is an essential one in agriculture. Crop yield protection is the science
and practice of handling plant diseases, weeds, and other pests. Accurate information …

A general purpose multi-fruit system for assessing the quality of fruits with the application of recurrent neural network

B Dhiman, Y Kumar, YC Hu - Soft Computing, 2021 - Springer
In the industry of agricultural farming, defected fruits are the major reason for financial
calamities across the globe. It affects both the quality and competence of the fruits. Quality …