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..
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..
ATT Squeeze U-Net A Lightweight Network for Forest Fire Detection and Recognition
Aim: To efficient CNN based system for fire detection in videos captured in uncertain surveillance scenariosSynopsis: Vision based fire detection framework has lately picked up popularity when contrasted ..
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..
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..
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..
Convolution neural network based enhanced computerized Technique for brain tumour detection
Aim: To detect and identify the Brain Tumor using Deep-Learning techniquesSynopsis: Brain is the controlling unit of human body. It regulates the functions such as memory, vision, hearing, knowledge, personality, problem solving etc. ..
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..