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..
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..
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..
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, in the civil field, ship detection plays a strong supervisory r..
PestNet: An End-to-End Deep Learning Approach for Large-Scale Multi-Class Pest Detection and Classification
Aim: To detect and classify large-scale multi-class pest using Convolution Neural Network. Synopsis: Regarding the growth of crops, one of the important factor..
Aim: This paper aim to detect Real time driver's fatigue state using Convolutional Neural Network (CNN) Synopsis: Drowsy driving is one of the major causes of road accidents and death. Hence, detection of driver’s fati..
Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolution Neural Networks
Aim: To detect the apple leaf diseases using convolutional neural network for high accuracy detectionSynopsis: Plant diseases are a major threat to plant growth and crop yield and many researchers have expended subs..
Synopsis: Pedestrian detection has made significant advances benefiting from the region-based convolutional neural networks (R-CNN). The project introduces a strict matching metric, which is beneficial to selecting well-aligned positive samples A positive sample matches a ground truth only i..