Industrial Quality Prediction System through Data Mining Algorithm
Volume-3 | Issue-2
Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2
Nakagami-m Fading Detection with Eigen Value Spectrum Algorithms
Volume-3 | Issue-2
Abstractive Summarization System
Volume-3 | Issue-4
Design of Adaptive Estimator for Nonlinear control system in Noisy Domain
Volume-3 | Issue-3
Automated Nanopackaging using Cellulose Fibers Composition with Feasibility in SEM Environment
Volume-3 | Issue-2
Comparative Analysis of Temperature Measurement Methods based on Degree of Agreement
Volume-3 | Issue-3
Transistor Sizing using Hybrid Reinforcement Learning and Graph Convolution Neural Network Algorithm
Volume-3 | Issue-3
A Review on Meshing Techniques in Biomedicine
Volume-3 | Issue-4
EL DAPP - An Electricity Meter Tracking Decentralized Application
Volume-2 | Issue-1
SMART STREET SYSTEM WITH IOT BASED STREET LIGHT OPERATION AND PARKING APPLICATION
Volume-1 | Issue-1
ENERGY AND POWER EFFICIENT SYSTEM ON CHIP WITH NANOSHEET FET
Volume-1 | Issue-1
Abstractive Summarization System
Volume-3 | Issue-4
A Review on Meshing Techniques in Biomedicine
Volume-3 | Issue-4
MIMO BASED HIGH SPEED OPTICAL FIBER COMMUNICATION SYSTEM
Volume-1 | Issue-2
Industrial Quality Prediction System through Data Mining Algorithm
Volume-3 | Issue-2
Comparative Analysis of Temperature Measurement Methods based on Degree of Agreement
Volume-3 | Issue-3
Transistor Sizing using Hybrid Reinforcement Learning and Graph Convolution Neural Network Algorithm
Volume-3 | Issue-3
VIRTUAL REALITY SIMULATION AS THERAPY FOR POSTTRAUMATIC STRESS DISORDER (PTSD)
Volume-1 | Issue-1
Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2
Volume - 3 | Issue - 4 | december 2021
Published
27 April, 2022
This paper presents a model which is based on machine learning algorithms to detect brain tumours from magnetic resonance images with high accuracy. A Convolutional Neural Network (CNN) has been used as the algorithm for feature extraction, and segmentation. The dataset used has been acquired from an internet website. The results show that this technique is promising and the accuracy of 97.79% has been achieved.
KeywordsImage segmentation CNN Augmentation Image classification MRI
Full Article PDF Download Article PDF