However, plant identification becomes more challenging in case of leaves with the complicated background having interferences and overlapping. In this paper, an efficient approach is proposed for classification of leaf images with a complicated background. In the proposed approach, firstly, a saliency ...
In this research, we proposed using two methods for the problem of plant species identification from leaf patterns. Firstly, we use a traditional recognition shallow architecture with extracted features histogram of oriented gradients (HOG) vector, then those features used to classifying by SVM ...
Leaf identification helps you to identify plants just by taking a photo of them with your phone. Our AI technology will recognize what plant is this in a snap,…
Leaf venation extraction is not always possible since it is not always visible in photographic images. This study proposed a novel approach of leaf identification based on feature hierarchies. First, leaves were sorted by their overall shape using shape signatures. Then this sorted list was pruned ...
Therefore, related diseases for these plants were taken for identification. With very less computational efforts the optimum results were obtained, which also shows the efficiency of proposed algorithm in recognition and classification of the leaf diseases. Another advantage of using this method is that...
The main problem in using EF has been how to use its large coefficient matrix for object identification. Obviously, machine vision operations that precede leaf shape feature analysis may affect the usefulness of these methods for precision agriculture. We will assume that those machine vision ...
Leaf of different plants have different characteristics which can be used to classify them.This paper presents a simple and computationally efficient method for plant identification using digital image processing and machine vision technology. The proposed approach consists of three phases: pre-processing,...
In this paper, we proposed a novel plant leaf disease identification model based on a deep convolutional neural network (Deep CNN). The Deep CNN model is trained using an open dataset with 39 different classes of plant leaves and background images. Six types of data augmentation methods were ...
Plant diseases and pests are important factors determining the yield and quality of plants. Plant diseases and pests identification can be carried out by means of digital image processing. In recent years, deep learning has made breakthroughs in the fiel
In this study, the author has analyzed the literature on various plant leaf disease detections and classifications, as well as the models/techniques that have been used. According to [1], DL-based solutions for real-time insect detection and identification in the soybean crop have been proposed...