Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming
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 …
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …
Machine learning for smart agriculture and precision farming: towards making the fields talk
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 …
data tsunami. In addition, man-to-machine digital data handling has magnified the …
Application of smart techniques, internet of things and data mining for resource use efficient and sustainable crop production
Technological advancements have led to an increased use of the internet of things (IoT) to
enhance the resource use efficiency, productivity, and cost-effectiveness of agricultural …
enhance the resource use efficiency, productivity, and cost-effectiveness of agricultural …
A survey on image-based insect classification
Entomology has had many applications in many biological domains (ie insect counting as a
biodiversity index). To meet a growing biological demand and to compensate a decreasing …
biodiversity index). To meet a growing biological demand and to compensate a decreasing …
Automatic identification of tool wear based on convolutional neural network in face milling process
X Wu, Y Liu, X Zhou, A Mou - Sensors, 2019 - mdpi.com
Monitoring of tool wear in machining process has found its importance to predict tool life,
reduce equipment downtime, and tool costs. Traditional visual methods require expert …
reduce equipment downtime, and tool costs. Traditional visual methods require expert …
A comprehensive review of Data Mining techniques in smart agriculture
Agriculture remains a vital sector for most countries. It presents the main source of food for
the population of the world. However, it faces a big challenge: producing more and better …
the population of the world. However, it faces a big challenge: producing more and better …
Wireless sensor networks in agriculture through machine learning: A survey
MM Rahaman, M Azharuddin - Computers and Electronics in Agriculture, 2022 - Elsevier
This survey paper describes the concept of Wireless Sensor Networks (WSNs), Machine
Learning (ML) and their applications on various fields of smart agriculture. Here we first …
Learning (ML) and their applications on various fields of smart agriculture. Here we first …
Citrus pests and diseases recognition model using weakly dense connected convolution network
S Xing, M Lee, K Lee - Sensors, 2019 - mdpi.com
Pests and diseases can cause severe damage to citrus fruits. Farmers used to rely on
experienced experts to recognize them, which is a time consuming and costly process. With …
experienced experts to recognize them, which is a time consuming and costly process. With …
Rice blast recognition based on principal component analysis and neural network
M Xiao, Y Ma, Z Feng, Z Deng, S Hou, L Shu… - … and electronics in …, 2018 - Elsevier
Based on principal component analysis and back propagation neural network (PCA-BP), a
rice blast recognition method was proposed to solve the problems of low accuracy …
rice blast recognition method was proposed to solve the problems of low accuracy …
Selection for high quality pepper seeds by machine vision and classifiers
K TU, L LI, L YANG, J WANG, SUN Qun - Journal of Integrative Agriculture, 2018 - Elsevier
This research aimed to improve selection of pepper seeds for separating high-quality seeds
from low-quality seeds. Past research has shown that seed vigor is significantly related to …
from low-quality seeds. Past research has shown that seed vigor is significantly related to …