Grid View:

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..

A Smart Wireless System to Automate Production of Crops and Stop Intrusion Using Deep Learning


Aim:        Aim of the project is to reduce animal-vehicle collision on roadsides using machine learning and raspberry pi. Abstract:        Animal-Vehicle collisions are a significant public health concern in various countries. The annual economic cost exceeds over..

AF-DCGAN: Amplitude Feature Deep Convolutional GAN for Fingerprint Construction in Indoor Localization Systems


                                                Technology: DEEP LEARNING / GAN      ..

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 Integrated Task Model for Fake News Detection


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..

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..

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..

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..

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..

Cardiac-DeepIED: Automatic Pixel-Level Deep Segmentation for Cardiac Bi-Ventricle Using Improved End-to-End Encoder-Decoder Network


Abstract:              Accurate segmentation of cardiac bi-ventricle (CBV) from magnetic resonance (MR) images has a great significance to analyze and evaluate the function of the cardiovascular system. However, the majority of cardiac MR images show that the similar intensity distribu..

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