Analysis and Testing of Weed Real-time Identification Based on Neural Network
نویسندگان
چکیده
Contrasting the two green strength genes of soil, wheat, corn, and the weed, the paper designed a system to identify the weed from the crop. It used the 2GR-B and BP neural network, with the help of pixel-position-histogram diagram, to calculate the area and position of weeds. The result showed that it could identify the weed from the field and crop with an accuracy of 93%. The program gave the result that running time of identifying weed in wheat field was 273.31ms. As far as the corn was concerned, the time was 321.94ms, In a word, the system can satisfy the request of real-time.
منابع مشابه
Neural Network Performance Analysis for Real Time Hand Gesture Tracking Based on Hu Moment and Hybrid Features
This paper presents a comparison study between the multilayer perceptron (MLP) and radial basis function (RBF) neural networks with supervised learning and back propagation algorithm to track hand gestures. Both networks have two output classes which are hand and face. Skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...
متن کاملComparative Analysis of Neural Network Training Methods in Real-time Radiotherapy
Background: The motions of body and tumor in some regions such as chest during radiotherapy treatments are one of the major concerns protecting normal tissues against high doses. By using real-time radiotherapy technique, it is possible to increase the accuracy of delivered dose to the tumor region by means of tracing markers on the body of patients.Objective: This study evaluates the accuracy ...
متن کاملMarkovian Delay Prediction-Based Control of Networked Systems
A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order...
متن کاملDiscrimination of Power Quality Distorted Signals Based on Time-frequency Analysis and Probabilistic Neural Network
Recognition and classification of Power Quality Distorted Signals (PQDSs) in power systems is an essential duty. One of the noteworthy issues in Power Quality Analysis (PQA) is identification of distorted signals using an efficient scheme. This paper recommends a Time–Frequency Analysis (TFA), for extracting features, so-called "hybrid approach", using incorporation of Multi Resolution Analysis...
متن کاملExperimental and finite-element free vibration analysis and artificial neural network based on multi-crack diagnosis of non-uniform cross-section beam
Crack identification is a very important issue in mechanical systems, because it is a damage that if develops may cause catastrophic failure. In the first part of this research, modal analysis of a multi-cracked variable cross-section beam is done using finite element method. Then, the obtained results are validated usingthe results of experimental modal analysis tests. In the next part, a nove...
متن کامل