Design and Development of Machine Learning based Expert System for Epileptic Seizure Diagnosis and Classification Process

2021 ◽  
Author(s):  
Tushar Vats ◽  
Chetan Kumar
Keyword(s):  
Machine Learning ◽  
Expert System ◽  
Epileptic Seizure ◽  
Design And Development ◽  
Diagnosis And Classification

scholarly journals A review of epileptic seizure detection using machine learning classifiers

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammad Khubeb Siddiqui ◽  
Ruben Morales-Menendez ◽  
Xiaodi Huang ◽  
Nasir Hussain
Keyword(s):  
Machine Learning ◽  
Epileptic Seizure ◽  
Seizure Detection ◽  
Epileptic Seizure Detection ◽  
Machine Learning Classifiers ◽  
Learning Classifiers

Design Simulation and Assessment of EEG Based Expert System for Classification and Detection of Epileptic Seizure

2021 ◽  
Author(s):  
Anson Antony ◽  
Shreeanant Bharadwaj ◽  
Shivam Sonawane ◽  
Nishitha Chidipothu ◽  
Yash Kothari ◽  
...  
Keyword(s):  
Expert System ◽  
Epileptic Seizure

An Extensive Review on Machine Learning and Deep Learning Based Cervical Cancer Diagnosis and Classification Models

2020 ◽  
Vol 17 (12) ◽  
pp. 5438-5446
Author(s):  
C. Suguna ◽  
S. P. Balamurugan
Keyword(s):  
Machine Learning ◽  
Cervical Cancer ◽  
Deep Learning ◽  
Comparative Study ◽  
Cancer Diagnosis ◽  
Pap Smear ◽  
Classification Models ◽  
Extensive Review ◽  
Diagnosis And Classification ◽  
Automated Machine Learning

Cervical cancer is a commonly occurring deadliest disease among women, which needs earlier diagnosis to reduce the prevalence. Pap-smear is considered as a widely employed technique to screen and diagnose cervical cancer. Since classical manual screening techniques are inefficient in the identification of cervical cancer, several research works have been started to develop automated machine learning (ML) and deep learning (DL) tools for cervical cancer diagnosis. This paper surveys the recent works made on cervical cancer diagnosis and classification. The recently presently ML and DL models for cervical cancer diagnosis and classification has been reviewed in detail. Besides, segmentation techniques developed for cervical cancer diagnosis also surveyed. At the end of the survey, a brief comparative study has been carried out to identify the significance of the reviewed methods.

scholarly journals Development of Continuum Robot Arm and Gripper for Harvesting Cherry Tomatoes

2019 ◽  
Author(s):  
Azamat Yeshmukhametov ◽  
Koichi Koganezawa ◽  
Zholdas Buribayev ◽  
Yedilkhan Amirgaliyev ◽  
Yoshio Yamamoto
Keyword(s):  
Machine Learning ◽  
Recognition System ◽  
Stem Cutting ◽  
Robot Arm ◽  
Design And Development ◽  
Challenging Issue ◽  
Continuum Robot ◽  
Unstructured Environment ◽  
Backbone Structure ◽  
Cherry Tomatoes

Designing and development of agricultural robot is always a challenging issue, because of robot intends to work an unstructured environment and at the same time, it should be safe for the surrounded plants. Therefore, traditional robots cannot meet the high demands of modern challenges, such as working in confined and unstructured workspaces. Based on current issues, we developed a new tomato harvesting wire-driven discrete continuum robot arm with a flexible backbone structure for working in confined and extremely constrained spaces. Moreover, we optimized a tomato detaching process by using newly designed gripper with passive stem cutting function. Moreover, by designing the robot we also developed ripe tomato recognition by using machine learning. This paper explains the proposed continuum robot structure, gripper design, and development of tomato recognition system.

Sign in / Sign up

Export Citation Format

Share Document