An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Energy Management System in the Vehicles using Three Level Neuro Fuzzy Logic
Volume-3 | Issue-3
Cloud Load Estimation with Deep Logarithmic Network for Workload and Time Series Optimization
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Population Based Meta Heuristics Algorithm for Performance Improvement of Feed Forward Neural Network
Volume-2 | Issue-1
Comparative Analysis of an Efficient Image Denoising Method for Wireless Multimedia Sensor Network Images in Transform Domain
Volume-3 | Issue-3
A Comprehensive Review on Power Efficient Fault Tolerance Models in High Performance Computation Systems
Volume-3 | Issue-3
An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet
Volume-3 | Issue-4
An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Effective Prediction of Online Reviews for Improvement of Customer Recommendation Services by Hybrid Classification Approach
Volume-3 | Issue-4
Acoustic Features Based Emotional Speech Signal Categorization by Advanced Linear Discriminator Analysis
Volume-3 | Issue-4
Analysis of Statistical Trends of Future Air Pollutants for Accurate Prediction
Volume-3 | Issue-4
Identification of Electricity Threat and Performance Analysis using LSTM and RUSBoost Methodology
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Volume - 4 | Issue - 1 | march 2022
Published
28 April, 2022
Estimating crop creation has been a consistent worry since the start of the historical backdrop of agribusiness. Guaging strategies have advanced, as has horticulture itself and the determinations of the gauges required. The individuals who utilize figure information are continuously looking for more noteworthy precision, granularity, likeness, and idealness. The people who produce the information or add to their creation generally work under monetary and specialized requirements. Acquiring opportune information presents an undeniable test. Today, the human, institutional, specialized, and monetary foundation behind crop figures and proposal gauges specifically can be unquestionably complicated. This distribution gives experiences into such complex information frameworks at the nation level. It features great practices and prospects for what's to come. The distinguishing proof and location of sicknesses of plants is one of the central matters which decide the deficiency of the suggestion of yield creation and agribusiness. The investigations of plant illness are the examination of any noticeable places in any part of the plant, such as any spots or conceals, which assists in distinguishing between two plants. The manageability of the plant is one of the central issues for rural turn of events. The discovery of plant sicknesses is undeniably challenging to get right. The recognizable proof of the illness requires loads of work and ability, bunches of information in the field of plants and the investigations of the identification of those sicknesses. Thus, picture handling is utilized for the identification of plant infections. The detection of infections follows the strategies for picture procurement, picture extraction, picture division, and picture pre-handling.
KeywordsMachine Learning crop production image pre-processing crop recommendation prediction
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