A comprehensive survey on support vector machine classification: Applications, challenges and trends

J Cervantes, F Garcia-Lamont, L Rodríguez-Mazahua… - Neurocomputing, 2020 - Elsevier
In recent years, an enormous amount of research has been carried out on support vector
machines (SVMs) and their application in several fields of science. SVMs are one of the …

[HTML][HTML] Field programmable gate array applications—A scientometric review

J Ruiz-Rosero, G Ramirez-Gonzalez, R Khanna - Computation, 2019 - mdpi.com
Field Programmable Gate Array (FPGA) is a general purpose programmable logic device
that can be configured by a customer after manufacturing to perform from a simple logic gate …

Diagnosis of skin cancer using machine learning techniques

A Murugan, SAH Nair, AAP Preethi… - Microprocessors and …, 2021 - Elsevier
Generally, skin disease is a common one in human diseases. In computer vision application,
the skin color is the powerful indication for this disease. This system identifies the skin …

CCII and FPGA Realization: A Multistable Modified Fourth‐Order Autonomous Chua's Chaotic System with Coexisting Multiple Attractors

F Yu, H Shen, L Liu, Z Zhang, Y Huang, B He… - …, 2020 - Wiley Online Library
In this paper, a multistable modified fourth‐order autonomous Chua's chaotic system is
investigated. In addition to the dynamic characteristics of the third‐order Chua's chaotic …

FPGA implementations of SVM classifiers: A review

S Afifi, H GholamHosseini, R Sinha - SN Computer Science, 2020 - Springer
Support vector machine (SVM) is a robust machine learning model with high classification
accuracy. SVM is widely utilized for online classification in various real-time embedded …

EEG signal classification using a novel universum-based twin parametric-margin support vector machine

BB Hazarika, D Gupta, B Kumar - Cognitive Computation, 2023 - Springer
The Universum data, which indicates a sample that does not belong to any of the classes,
has been proved to be useful in supervised learning. The researchers have explored the …

FPGA-based implementation of classification techniques: A survey

A Saidi, SB Othman, M Dhouibi, SB Saoud - Integration, 2021 - Elsevier
Recently, a number of classification techniques have been introduced. However, processing
large dataset in a reasonable time has become a major challenge. This made classification …

Toward a development of general type-2 fuzzy classifiers applied in diagnosis problems through embedded type-1 fuzzy classifiers

E Ontiveros-Robles, P Melin - Soft Computing, 2020 - Springer
Nowadays, with the emergence of computer-aided systems, diagnosis problems are one of
the most important application areas of artificial intelligence. The present paper is focused …

[HTML][HTML] Parallel implementation on FPGA of support vector machines using stochastic gradient descent

FF Lopes, JC Ferreira, MAC Fernandes - Electronics, 2019 - mdpi.com
Sequential Minimal Optimization (SMO) is the traditional training algorithm for Support
Vector Machines (SVMs). However, SMO does not scale well with the size of the training set …

Varying combination of feature extraction and modified support vector machines based prediction of myocardial infarction

AR Sulthana, AK Jaithunbi - Evolving systems, 2022 - Springer
Today's food habits, way of life causes a number of health disorders in human especially
those related to heart diseases. Cardiac arrest is one such disease, which is the deadliest …