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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..

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..

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..

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..

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..

Technology: Deep Learning                                                   Tool: MATLAB R2018aObjective..

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:               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..

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..

Aim: To detect the diabetic retinopathy disease in the earlier stage using Deep learning method Synopsis: Diabetic Retinopathy is a disease that can lead to partial or complete blindness. Research shows that it contributes around 5 percent of the total cases of blindness. Usually it takes about two weeks for the diagnosis of disease; time and money..

Alternative title:  Social and Emotional Context analysis using Gradient Boosted SAM algorithm                                          ..

Aim:          To predict an emoji based on text, image and emojis Abstract:           Emojis are a very important part of communication in today’s world. It is used to express emotions during a conversation. We collect data from the twitter. Building a system wh..

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..