Liver segmentation and classification in computed tomography images using convolutional neural network and comparison of accuracy with support vector machine
NN Reddy, G Ramkumar - AIP Conference Proceedings, 2023 - pubs.aip.org
The goal of this research is to assess the presentation of convolutional Neural Network
(CNN) and SVM cla ssifiers in the new liver segmentation categorization using CT images …
(CNN) and SVM cla ssifiers in the new liver segmentation categorization using CT images …
Power Theft Detection Using Novel Linear SVM Algorithm and Compared With Convolutional SVM Algorithm For Accuracy
KB Reddy, MV Priya - 2022 14th International Conference on …, 2022 - ieeexplore.ieee.org
The aim of the study is to eliminate the electricity loss of individual customers and to
overcome the economic crisis. A novel Linear Support Vector Machine (SVM) algorithm is …
overcome the economic crisis. A novel Linear Support Vector Machine (SVM) algorithm is …
Return Loss Reduction of Dual Band Microstrip Antenna using Rectangular Patch in Comparison with Triangle Patch Antenna
PA Khan, M Raja, AM George - 2022 14th International …, 2022 - ieeexplore.ieee.org
Object of the study is to design and analyze a novel dual band rectangular microstrip patch
antenna for 3.8 GHz and 5 GHz to reduce the return loss (dB) when compared to the triangle …
antenna for 3.8 GHz and 5 GHz to reduce the return loss (dB) when compared to the triangle …
Design of Micro-Strip Patch Antenna using Metamaterial Substrate to improve the Directivity compared to FR4 Substrate
GAU Kiran, K Chanthirasekaran… - … Conference on Cyber …, 2022 - ieeexplore.ieee.org
The main aim of the study is to design a novel meta-material substrate microstrip patch
antenna (ArIon Diclad (870)) to improve the directivity compared to the FR4 substrate an …
antenna (ArIon Diclad (870)) to improve the directivity compared to the FR4 substrate an …
Classification of Brain Tumor Images with Improved Accuracy Using KNN and Comparing with SVM
CHS Raju, R Baskar, SK Tiwari - 2022 14th International …, 2022 - ieeexplore.ieee.org
The main object of the study is to evaluate the correctness parameter of brain MRI images
using KNN compared to SVM. The KNN algorithm has good accuracy in MRI images …
using KNN compared to SVM. The KNN algorithm has good accuracy in MRI images …
Human iris recognition under uncontrolled environment using convolutional neural network and compare accuracy with hidden Markov model classifier
B Karthik, G Ramkumar - AIP Conference Proceedings, 2023 - pubs.aip.org
The primary goal of this research is to evaluate the accuracy of human iris recognition using
a Convolutional Neural Network in an uncontrolled environment image to that of a Hidden …
a Convolutional Neural Network in an uncontrolled environment image to that of a Hidden …
Brain tumor detection using random forest algorithm in comparison with k-nearest neighbors algorithm to measure the accuracy, precision and recall
M Sandeep, A Deepak - AIP Conference Proceedings, 2023 - pubs.aip.org
The target of this work is to assess the presentation involving arbitrary woodland and
contrast and KNN for the recognition of mind growth with Novel division. In this work, an AI …
contrast and KNN for the recognition of mind growth with Novel division. In this work, an AI …
Detection of ethanol quality using support vector machine in comparison with naive bayes classifier to measure accuracy
R Manikanta, A Rag S - AIP Conference Proceedings, 2023 - pubs.aip.org
The aim of this article is to evaluate the quality of ethanol using SVM (Support Vector
Machine) by comparing it with the Naive Bayes algorithm for detection of ethanol quality …
Machine) by comparing it with the Naive Bayes algorithm for detection of ethanol quality …
Evaluation of Cup to Disc Ratio for Glaucoma detection through optic cup and disc segmentation using Fuzzy C-means clustering and comparing with adaptive …
CHV Reddy, K Vidhya… - 2022 14th International …, 2022 - ieeexplore.ieee.org
The objective of the study is to develop an automated approach for detecting Glaucoma from
fundus images by using Fuzzy c-means clustering (FCM) and comparing with adaptive …
fundus images by using Fuzzy c-means clustering (FCM) and comparing with adaptive …
Performance comparison of threshold segmentation algorithm with k-nearest neighbour for brain tumor detection
PM Kumar, V Amudha - AIP Conference Proceedings, 2023 - pubs.aip.org
The goal of this research is to compare the performance of the novel Threshold algorithm
segmentation method to K-NN for brain tumour detection. A total of 150 samples were …
segmentation method to K-NN for brain tumour detection. A total of 150 samples were …