Hispa rice disease classification using convolutional neural network
The current work focuses on implementing a rice disease detection (RDD) system on hispa
rice disease by using real-time rice plant images collected from rice fields of Punjab, trained …
rice disease by using real-time rice plant images collected from rice fields of Punjab, trained …
Rice Leaf blight Disease detection using multi-classification deep learning model
One of the main crops in agricultural fields is considered to be rice, which is produced and
used extensively over the world. Due to this very reason, there is always a high risk of rice …
used extensively over the world. Due to this very reason, there is always a high risk of rice …
Tomato spotted wilt disease severity levels detection: a deep learning methodology
V Salonki, A Baliyan, V Kukreja… - 2021 8th International …, 2021 - ieeexplore.ieee.org
The wide variety of diseases in the tomato plant affects the quality and quantity of the
production. To counteract the problem of disease in tomato plants deep learning (DL) based …
production. To counteract the problem of disease in tomato plants deep learning (DL) based …
Automatic classification of wheat rust diseases using deep convolutional neural networks
Wheat is the staple food for Indians and it is one of the most common grain crops all over the
world. The wheat diseases cause a huge amount of yield losses. The wheat yield losses are …
world. The wheat diseases cause a huge amount of yield losses. The wheat yield losses are …
Potato blight: deep learning model for binary and multi-classification
V Kukreja, A Baliyan, V Salonki… - 2021 8th International …, 2021 - ieeexplore.ieee.org
Detection of plant crop diseases has become an active field of research day by day due to
increasing the demand for such systems and techniques as crop diseases are now become …
increasing the demand for such systems and techniques as crop diseases are now become …
Detection of corn gray leaf spot severity levels using deep learning approach
A Baliyan, V Kukreja, V Salonki… - 2021 9th International …, 2021 - ieeexplore.ieee.org
A simple Convolutional neural network (CNN) based deep learning (DL) model has been
proposed for multi-classification of corn gray leaf spot (CGLS) disease based on five …
proposed for multi-classification of corn gray leaf spot (CGLS) disease based on five …
On-device object detection for more efficient and privacy-compliant visual perception in context-aware systems
I Rodriguez-Conde, C Campos, F Fdez-Riverola - Applied Sciences, 2021 - mdpi.com
Ambient Intelligence (AmI) encompasses technological infrastructures capable of sensing
data from environments and extracting high-level knowledge to detect or recognize users' …
data from environments and extracting high-level knowledge to detect or recognize users' …
Improving satellite image classification accuracy using GAN-based data augmentation and vision transformers
Deep learning (DL) algorithms have shown great potential in classifying satellite imagery but
require large amounts of labeled data to make accurate predictions. However, generating …
require large amounts of labeled data to make accurate predictions. However, generating …
Comparative study to detect driver drowsiness
Driver Drowsiness is one of the major causes of road accidents which leads to fatal and non-
fatal injuries, sudden deaths and substantial monetary losses. Recently, various approaches …
fatal injuries, sudden deaths and substantial monetary losses. Recently, various approaches …
Innovative synthetic data augmentation for dam crack detection, segmentation, and quantification
Although deep-learning-based approaches have demonstrated impressive performance in
object detection tasks, the requirement for large datasets of annotated training images limits …
object detection tasks, the requirement for large datasets of annotated training images limits …