Application‐Based Review of Soft Computational Methods to Enhance Industrial Practices Abetted by the Patent Landscape Analysis
S Tamilselvan, G Dhanalakshmi… - … : Data Mining and …, 2025 - Wiley Online Library
Soft computing is a collective methodology that touches all engineering and technology
fields owing to its easiness in solving various problems while comparing the conventional …
fields owing to its easiness in solving various problems while comparing the conventional …
[PDF][PDF] Detection of brain tumors from MRI using gaussian RBF kernel based support vector machine
Abstract The Support Vector Machine (SVM) is a powerful classification technique that has
been used extensively in the field of medical imaging. A model based on SVM with …
been used extensively in the field of medical imaging. A model based on SVM with …
Hybrid intelligent system for disease diagnosis based on artificial neural networks, fuzzy logic, and genetic algorithms
Disease diagnosis often involves acquiring medical images using devices such as MRI, CT
scan, x-ray, or mammograms of patients' organs. Though many medical diagnostic …
scan, x-ray, or mammograms of patients' organs. Though many medical diagnostic …
Fuzzy neural networks and genetic algorithms for medical images interpretation
N Benamrane, A Aribi, L Kraoula - Geometric Modeling and …, 2006 - ieeexplore.ieee.org
In this paper, we propose an approach for detection and specification of anomalies present
in medical images. The idea is to combine three metaphors: neural networks, fuzzy logic and …
in medical images. The idea is to combine three metaphors: neural networks, fuzzy logic and …
[PDF][PDF] Fault detection and classification in power electronic circuits using wavelet transform and neural network
V Prasannamoorthy, N Devarajan - Journal of Computer Science, 2011 - Citeseer
Problem statement: The identification of faults in any analog circuit is highly required to
ensure the reliability of the circuit. Early detection of faults in a circuit can greatly assist in …
ensure the reliability of the circuit. Early detection of faults in a circuit can greatly assist in …
Establishing a database for sickle cell disease patient map** and survival tracking: The sickle pan-african research consortium Nigeria example
Background: The Sickle Pan-African Research Consortium (SPARCO) and Sickle Africa
Data Coordinating Center (SADaCC) were set up with funding from the US National Institute …
Data Coordinating Center (SADaCC) were set up with funding from the US National Institute …
Automated segmentation of brain tumor using optimal texture features and support vector machine classifier
This paper presents a new general automatic method for segmenting brain tumors in
magnetic resonance (MR) images. Our approach addresses all types of brain tumors. The …
magnetic resonance (MR) images. Our approach addresses all types of brain tumors. The …
Soft computing in medical diagnostic applications: A short review
Medical diagnosis is one of the most important issues in healthcare. Computer aided
systems have been developed in order to diagnose diseases by examining the internal …
systems have been developed in order to diagnose diseases by examining the internal …
Brain tumour diagnostic segmentation based on optimal texture features and support vector machine classifier
A Kharrat, M BenMessaoud… - International Journal of …, 2014 - inderscienceonline.com
This paper presents a new general automatic method for segmenting brain tumours in
Magnetic Resonance (MR) images. Our approach addresses all types of brain tumours. The …
Magnetic Resonance (MR) images. Our approach addresses all types of brain tumours. The …
An accurate thresholding-based segmentation technique for natural images
Segmentation is a process of dividing an image into distinct regions with the aim to extracts
object of interest from the background. The traditional thresholding and clustering …
object of interest from the background. The traditional thresholding and clustering …