A Breast Cancer Diagnosis Method based on VIM Feature Selection and Hierarchical Clustering Random Forest Algorithm
Aim: To detect the breast cancer using K Nearest Neighbor algorithms with the help of data mining techniques. Abstract: Breast cancer is one of the most common cancers among the women. Breast c..
A Comparative Study of Deep Learning Networks for COVID-19 Recognition in Chest X-ray Images
Aim: To detect the COVID-19 using x-ray images by using Convolutional neural network. Abstract: The Corona-virus 2019(COVID-19), which first occurs in Wuhan city of China in December 2019, spread quickly around the world and became a plague. Due to the r..
A Crop Pest Classification Model Using Deep Learning Techniques
Aim: To detect and classify large-scale multi-class pest using Convolution Neural Network. Synopsis: Regarding the growth of crops, one of the important factors affecting crop yield is insect disasters. Since most insect species are extremely similar, insect detection on field crops, such as rice, soybean and other crops, is more challenging than g..
A Machine Learning-Based Classification and Prediction Technique for DDoS Attacks
Aim: We proposed a complete systematic approach to detect DDOS attack using machine learning algorithm.Abstract: Distributed network attacks are referred to as Distributed Denial of Service (DDoS) attacks. These attacks take advantage of specific limitations t..
A Rotational Libra R-CNN Method for Ship Detection
Aim: To automate the detection of presence of ships and to classify the types of ships available in the given Image. Synopsis: The detection of inshore and offshore ships is an essential task for a large variety of applications in both military and civilian fields. For example..
Accident Prevention and Detection System using IoT Integrated in an Electric Pole
Objective: The mainstay of the project is to design and develop a system is to prevent accidents occurring due to unaware of the vehicles approaching from other turns towards them, using IoT.Introduction:In today’s world, the technology has skyrocketed and has an impact on almost everyone’s life..
An Approach for Prediction of Loan Approval using Machine Learning Algorithm
Aim: To determine the loan approval system using machine learning algorithms.Abstract: Loan approval is a very important process for banking organizations. The systems approved or reject the loan applications. Recovery of loans is a ma..
An Automated System to Limit COVID-19 Using Facial Mask Detection in Smart City Network
Aim: To apply the Deep Learning techniques based on convolution neural network improving the face mask detector accuracy. Synopsis: The corona virus disease 2019 (COVID-19) has globally infected over 2.7million people and caused over 180..
An OCR Post-Correction Approach Using Deep Learning for Processing Medical Reports
Aim: Optical character recognition (OCR) can be used for the online retrieval of the printed material such as medical documents, forms, or applications for retrieving valuable information that was available in the printed documents. Deep learning approaches have been used to solve natural langua..
Automated Smart Attendance System Using Face Recognition
Aim: To detect and recognize the face using real time attendance system based on LBPH algorithm. Abstract: Face recognition can be considered one of the most successful biometric identification..
Big Data Analyzing Techniques in Mathematical House Price Prediction Model
Aim: As the house price prediction is vital for both the Ill-being of the public and the economic development, many experts in different research fields have explored and predicted it with the machine-learning strategies. Because the price is susceptible to multiple factors, it..
Blockchain-Based Public Integrity Verification for Cloud Storage against Procrastinating auditors
Aim: The main aim of this project is to provide a reliable and secure cloud service and also increase trustworthiness of certifications by Continuous Auditing.Introduction: An increasing number of organizations outsource their data, applications and bu..
Brain Tumor Detection and Classification Using Convolutional Neural Network (CNN)
Aim: To detect and identify the Brain Tumor using Deep-Learning techniques.Abstract: Medical image processing is that the one among the foremost demanding and promising field nowada..
Brain Tumor Identification and Classification of MRI images using deep learning techniques
Aim: To detect and identify the Brain Tumor using Deep-Learning techniques Abstract:Brain is the controlling unit of human body. It regulates the functions such as memory, vision, hearing, knowledge, personality, problem solving etc. The main reason for brain tumors is the uncontrolled development of brain cells. In medical practices..
Breast Cancer Detection Using Extreme Learning machine Based on Feature Fusion with CNN Deep Features
Aim: To classify benign and malignant breast masses using K Nearest Neighbor based on Feature Fusion with CNN Deep Features.Synopsis: A computer-aided diagnosis (CAD) system based on mammogram..