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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 Lightweight Convolutional Neural Network for Real-Time Facial Expression Detection
Aim: To recognize the real time facial expression using Deep learning technique.Abstract: In today’s world, there is a tremendous increase in usage of machinery. The world needs machines to understand humans and interpret ac..
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..
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..
Automatic Detection and Monitoring of Diabetic Retinopathy Using Efficient Convolutional NeuralNetworks
Aim: This paper aim to detect the diabetic disease identification using deep learning methods. Abstract: Diabetic Retinopathy is a complication of diabetes that is caused due to the changes in the blood vessels of the retina and is one of the leading causes of blindness in th..
Crop Yield Prediction based on Indian Agriculture using Machine Learning
Aim: To be precise and accurate in predicting crop yield and deliver the end user with proper recommendations about required fertilizer ratio based on soil parameters.Abstract India is the land of agriculture and it is the major source of economy.70% of Ind..
Deep Convolutional Neural Network for Fire Detection
Aim: To efficient RCNN based system for fire detection in videos captured in uncertain surveillance scenarios Synopsis: Vision based fire detection framework has lately picked up popularity when contrasted with cus..
Deep Learning based Automatic Multi-Class Wild Pest Monitoring Approach using Hybrid Global and Local Activated Features
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..
Deep Neural Architecture for Face mask Detection on Simulated Masked Face Dataset against Covid-19 Pandemic
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..
Detection of Social Network Spam Based on Improved Extreme Learning Machine
Aim: To enhance the assigning accuracy of former methods in spam detection in Twitter using advanced methods.Synopsis: Social networking sites have become very popular in recent years. Users use them to find new frie..
Driver-Drowsiness Detection System Using Facial Features
Aim: This paper aim to detect Real time driver's fatigue state using Convolutional Neural Network (CNN) Synopsis: Accidents are more due to the driver’s drowsiness; it has been recorded that more than 40% of chances that acciden..
Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques
Aim: To apply machine learning techniques result in improving the accuracy in the prediction of cardiovascular disease.Abstract: Heart disease is one of the most significant problem is arising in the world today. Cardiovascu..
Lung Lesion Localization of COVID-19 From Chest CT Image: A Novel Weakly Supervised Learning Method
Aim: To detect the COVID-19 using CT 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 an..