Convolutional neural networks in detection of plant leaf diseases: A review
Rapid improvements in deep learning (DL) techniques have made it possible to detect and
recognize objects from images. DL approaches have recently entered various agricultural …
recognize objects from images. DL approaches have recently entered various agricultural …
DeepThink IoT: the strength of deep learning in internet of things
Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …
revolutionized technology in the twenty-first century, enabling humans and machines to …
Recognition of leaf disease using hybrid convolutional neural network by applying feature reduction
Agriculture is crucial to the economic prosperity and development of India. Plant diseases
can have a devastating influence towards food safety and a considerable loss in the …
can have a devastating influence towards food safety and a considerable loss in the …
Lightweight dense-scale network (LDSNet) for corn leaf disease identification
W Zeng, H Li, G Hu, D Liang - Computers and Electronics in Agriculture, 2022 - Elsevier
The identification of corn leaf diseases in real scenarios faces important challenges, such as
complex background interference, intra-and inter-class scale changes, and lightweight …
complex background interference, intra-and inter-class scale changes, and lightweight …
[HTML][HTML] PLDPNet: End-to-end hybrid deep learning framework for potato leaf disease prediction
Agricultural productivity plays a vital role in global economic development and growth. When
crops are affected by diseases, it adversely impacts a nation's economic resources and …
crops are affected by diseases, it adversely impacts a nation's economic resources and …
A systematic review of different categories of plant disease detection using deep learning-based approaches
Artificial intelligence has a significant impact on all sectors. It is revolutionizing agriculture by
replacing traditional methods with more efficient techniques and helping the world improve …
replacing traditional methods with more efficient techniques and helping the world improve …
DFCANet: A novel lightweight convolutional neural network model for corn disease identification
Y Chen, X Chen, J Lin, R Pan, T Cao, J Cai, D Yu… - Agriculture, 2022 - mdpi.com
The identification of corn leaf diseases in a real field environment faces several difficulties,
such as complex background disturbances, variations and irregularities in the lesion areas …
such as complex background disturbances, variations and irregularities in the lesion areas …
Corn emergence uniformity estimation and mapping using UAV imagery and deep learning
Abstract Assessment of corn (Zea Mays L.) emergence uniformity is important to evaluate
crop yield potential. Previous studies have shown the potential of unmanned aerial vehicle …
crop yield potential. Previous studies have shown the potential of unmanned aerial vehicle …
Feature fusion and kernel selective in Inception-v4 network
F Chen, J Wei, B Xue, M Zhang - Applied Soft Computing, 2022 - Elsevier
In recent years, deep learning has been developed very quickly, and related research has
shown a blossoming scene. Inception-v4 is a wide and deep network with good …
shown a blossoming scene. Inception-v4 is a wide and deep network with good …
Side-scan sonar image classification based on style transfer and pre-trained convolutional neural networks
Q Ge, F Ruan, B Qiao, Q Zhang, X Zuo, L Dang - Electronics, 2021 - mdpi.com
Side-scan sonar is widely used in underwater rescue and the detection of undersea targets,
such as shipwrecks, aircraft crashes, etc. Automatic object classification plays an important …
such as shipwrecks, aircraft crashes, etc. Automatic object classification plays an important …