Covid-19 Classification and Detection Model using Deep Learning
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..
Cursive Text Recognition in Natural Scene Images Using Deep Convolutional Recurrent Neural Network
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..
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 Ensemble Machine for Video Classification
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..
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 Learning COVID-19 Features on CXR Using Limited Training Data Sets
Technology: Deep Learning Tool: MATLAB R2018aObjective..
Deep Learning-Based Workers Safety Helmet Wearing Detection on Construction Sites Using Multi-Scale Features
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 ..
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..
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..
Efficient Classification Of Diabetic Retinopathy Using Binary Cnn
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..
EmoBed Strengthening Monomodal Emotion Recognition via Training with Crossmodal Emotion Embeddings
Alternative title: Social and Emotional Context analysis using Gradient Boosted SAM algorithm  ..
Emoji Prediction from Twitter Data using Deep Learning Approach
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..
Facemask Wearing Alert System Based on Simple Architecture With Low-Computing Devices
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..
Forest-Fire Response System Using Deep-Learning-Based Approaches With CCTV Images and Weather Data
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..