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..
Aim: To enhance the assigning accuracy of former methods in fake news detection using advanced methods.Abstract: We are in the age of information, everytime we read a piece of information or watch the news on TV, we look fo..
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..
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..
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..
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..
Comparative Analysis of Vehicle-Based and Driver-Based Features for Driver Drowsiness Monitoring by Support Vector Machines
Aim: This paper aim to detect Driver Drowsiness Detection by using support Vector Machines.Abstract: Driver drowsiness is a serious threat to road safety. Most driver monitoring systems (DMSs) already embedded in vehicles to detect drowsiness use vehicle-based feat..
Aim: To detect the COVID-19 using x-ray images by using Convolutional neural networkAbstract: The Corona-virus 2019(COVID-19), which first occurs in Wuhan city of China in December 2019, spread quickly around the world..
Aim: Text recognition in natural scene images is a challenging problem in computer vision. Text recognition in natural scene images is more complex due to variations in text size, colors, fonts, orientations, complex backgrounds, occlusion, illuminations and uneven lighting condition..
Deep Learning-Based Workers Safety Helmet Wearing Detection on Construction Sites Using Multi-Scale Features
Abstract: Due to a lack of knowledge about safety helmets, accidents and injuries on construction sites are now increasingly common. Worker supervision by hand is challenging and ineffective. Workers often take off the helmets because of weak security-conscious and discomfort, then ..
Aim: Electro-cardiogram (ECG) detect cardiovascular disease. In this work, the power of deep learning techniques was used to predict the four major cardiac abnormalities.Abstract: Cardiovascular diseases (heart diseases) are the leading cause of death worldwid..
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 180,000 d..
Aim: To efficient RCNN based system for fire detection in videos captured in uncertain surveillance scenariosSynopsis: Vision based fire detection framework has lately picked up popularity when contrasted with customa..
Aim: To detect the plant leaf diseases using neural network for high accuracy detectionSynopsis: To ensure global food security and the overall profit of stakeholders, the importance of correctly detecting and classify..
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 militar..