A survey of deep learning techniques for weed detection from images
The rapid advances in Deep Learning (DL) techniques have enabled rapid detection,
localisation, and recognition of objects from images or videos. DL techniques are now being …
localisation, and recognition of objects from images or videos. DL techniques are now being …
A novel deep learning method for detection and classification of plant diseases
The agricultural production rate plays a pivotal role in the economic development of a
country. However, plant diseases are the most significant impediment to the production and …
country. However, plant diseases are the most significant impediment to the production and …
[HTML][HTML] Review of weed recognition: A global agriculture perspective
Recent years have seen the emergence of various precision weed management
technologies in both research and commercial contexts. These technologies better target …
technologies in both research and commercial contexts. These technologies better target …
Artificial intelligence-based drone system for multiclass plant disease detection using an improved efficient convolutional neural network
The role of agricultural development is very important in the economy of a country. However,
the occurrence of several plant diseases is a major hindrance to the growth rate and quality …
the occurrence of several plant diseases is a major hindrance to the growth rate and quality …
Resnet-based modified red deer optimization with DLCNN classifier for plant disease identification and classification
SRG Reddy, GPS Varma, RL Davuluri - Computers and Electrical …, 2023 - Elsevier
The manual inspections of plant diseases resulted in low accuracy with high time
consumption and unable to predict the multiple diseases of plants. To address these …
consumption and unable to predict the multiple diseases of plants. To address these …
Weed classification from natural corn field-multi-plant images based on shallow and deep learning
Crop and weed discrimination in natural field environments is still challenging for
implementing automatic agricultural practices, such as weed control. Some weed control …
implementing automatic agricultural practices, such as weed control. Some weed control …
DCNet: DenseNet-77-based CornerNet model for the tomato plant leaf disease detection and classification
Early recognition of tomato plant leaf diseases is mandatory to improve the food yield and
save agriculturalists from costly spray procedures. The correct and timely identification of …
save agriculturalists from costly spray procedures. The correct and timely identification of …
Towards deep learning based smart farming for intelligent weeds management in crops
Introduction Deep learning (DL) is a core constituent for building an object detection system
and provides a variety of algorithms to be used in a variety of applications. In agriculture …
and provides a variety of algorithms to be used in a variety of applications. In agriculture …
Feature mapping for rice leaf defect detection based on a custom convolutional architecture
Rice is a widely consumed food across the world. Whilst the world recovers from COVID-19,
food manufacturers are looking to enhance their quality inspection processes for satisfying …
food manufacturers are looking to enhance their quality inspection processes for satisfying …
Performances of the lbp based algorithm over cnn models for detecting crops and weeds with similar morphologies
Weed invasions pose a threat to agricultural productivity. Weed recognition and detection
play an important role in controlling weeds. The challenging problem of weed detection is …
play an important role in controlling weeds. The challenging problem of weed detection is …