Technological revolutions in smart farming: Current trends, challenges & future directions
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 …
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …
Machine learning for plant breeding and biotechnology
M Niazian, G Niedbała - Agriculture, 2020 - mdpi.com
Classical univariate and multivariate statistics are the most common methods used for data
analysis in plant breeding and biotechnology studies. Evaluation of genetic diversity …
analysis in plant breeding and biotechnology studies. Evaluation of genetic diversity …
Research on deep learning in apple leaf disease recognition
Y Zhong, M Zhao - Computers and electronics in agriculture, 2020 - Elsevier
The main reason affecting apple production is the occurrence of apple leaf diseases, which
causes huge economic losses every year. Therefore, it is of great significance to study the …
causes huge economic losses every year. Therefore, it is of great significance to study the …
BreastNet: A novel convolutional neural network model through histopathological images for the diagnosis of breast cancer
Breast cancer is one of the most commonly diagnosed cancer types in the woman and
automatically classifying breast cancer histopathological images is an important task in …
automatically classifying breast cancer histopathological images is an important task in …
PlantDiseaseNet: Convolutional neural network ensemble for plant disease and pest detection
Plant diseases and pests cause significant losses in agriculture, with economic, ecological
and social implications. Therefore, early detection of plant diseases and pests via automated …
and social implications. Therefore, early detection of plant diseases and pests via automated …
Dry bean cultivars classification using deep cnn features and salp swarm algorithm based extreme learning machine
Since dry bean varieties have different qualities and economic values, their separation is of
great importance in the field of agriculture. In recent years, the use of artificial intelligence …
great importance in the field of agriculture. In recent years, the use of artificial intelligence …
Detection of lung cancer on chest CT images using minimum redundancy maximum relevance feature selection method with convolutional neural networks
Lung cancer is a disease caused by the involuntary increase of cells in the lung tissue. Early
detection of cancerous cells is of vital importance in the lungs providing oxygen to the …
detection of cancerous cells is of vital importance in the lungs providing oxygen to the …
Classification of white blood cells using deep features obtained from Convolutional Neural Network models based on the combination of feature selection methods
White blood cells are cells in the blood and lymph tissue produced by the bone marrow in
the human body. White blood cells are an important part of the immune system. The most …
the human body. White blood cells are an important part of the immune system. The most …
Real-time recognition system of soybean seed full-surface defects based on deep learning
G Zhao, L Quan, H Li, H Feng, S Li, S Zhang… - … and Electronics in …, 2021 - Elsevier
Accurately sorting high-quality soybean seeds is a key task in increasing soybean yield in
the breeding industry. At present, sorting systems based on machine vision focus on the …
the breeding industry. At present, sorting systems based on machine vision focus on the …
Smart farming becomes even smarter with deep learning—a bibliographical analysis
Z Ünal - IEEE access, 2020 - ieeexplore.ieee.org
Smart farming is a new concept that makes agriculture more efficient and effective by using
advanced information technologies. The latest advancements in connectivity, automation …
advanced information technologies. The latest advancements in connectivity, automation …