Aim: To automate the detection of presence of ships and to classify the types of ships available in the given Image. Synopsis: High resolution satellite image processing is one of the most growing fields in research today. There is so much to explore and so many ways to do it that it seems full of endless opportunities and possibilitie..
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 deaths. There are several similar large scale ser..
Aim: This mainstay of this paper is to detect the diabetic retinopathy disease identification using deep learning methods.Synopsis: Diabetic re..
Automatic Detection and Monitoring of DiabeticRetinopathy Using Efficient Convolutional NeuralNetworks and Contrast Limited Adaptive Histogram Equalization
Aim:This paper aim to detect the diabetic disease identification using deep learning methods.Synopsis: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 the developed world. Up to the present, Diabetic Retinopathy is still scre..
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 nowadays. Tumor is a rapid uncontrolled growth of cell. The tumor are often classified as benign, malignant and premalignant. When a tumor is noticed as maligna..
Breast Cancer Detection Using Extreme Learning machine Based on Feature Fusion with CNN Deep Features
Aim: To classify benign and malignant breast masses using machine learning algorithm based on Feature Fusion. Synopsis: Cancer is a class of diseases, which is driven by changing cell of the b..
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..
Aim: To detect the plant leaf diseases using convolutional neural network for high accuracy detection Synopsis: Plant diseases are a major threat to plant growth and crop yield and many researchers have e..
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 contrast..
Abstract: Video classiﬁcation has been extensively researched in computer vision due to its wide spread use in many important applications such as human action recognition and dynamic scene classiﬁcation. It is highly desired to have an end-to-end learning framework that can establish effective video r..
Deep Learning and Handcrafted Method Fusion: Higher Diagnostic Accuracy for Melanoma Dermoscopy Images
Abstract: Dermoscopy is an important tool in the early detection of melanoma, increasing the diagnostic accuracy over clinical visual inspection in the hands of experienced physicians. A pigment network whose structure varies in size and shape is called an irregular or a typical pigment network (AP..
Technology: Deep Learning Tool: MATLAB R2018aObjective..
Aim: To detected the Brain Tumor using Two-Pathway-Group Conventional Neural Networks.Synopsis: Brain tumor identification is really challenging task in early stages of life. But now it became advanced with deep-learning. Now a day’s issue of..
Aim: To mainstay of this project is to efficiently apply CNN for fire detection in videos captured in uncertain surveillance scenariosSynopsis: Tactile Internet can combine multiple technologies by enabling intellig..
Technology: Deep Learning &..