Deep Learning
A Lightweight Robust Deep Learning Model Gained High Accuracy in Classifying a Wide Range of Diabetic Retinopathy Images
Aim: To detect and identify the Diabetic disease detection using Deep-Learning techniques.Abstract: In the field of diabetic retinopathy detection, this study introduces a novel, lightweight, and robust deep learning model that achieves rema..
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 Integrated Multi-Task Model for Fake News Detection
Aim: To enhance the assigning accuracy of former methods in fake news detection using advanced methods.Abstract: We are in the age of information, everytime we read a piece of information or watch the news on TV, we look fo..
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 Detection and Classification Using Convolutional Neural Network (CNN)
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 nowada..
Brain Tumor Detection and Classification Using Intelligence Techniques An Overview
Aim: To detect and identify the Brain Tumor using Deep-Learning techniquesAbstract: 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 t..
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..
Comparative Analysis of Vehicle-Based and Driver-Based Features for Driver Drowsiness Monitoring by Support Vector Machines
Aim: This paper aim to detect Driver Drowsiness Detection by using support Vector Machines.Abstract: Driver drowsiness is a serious threat to road safety. Most driver monitoring systems (DMSs) already embedded in vehicles to detect drowsiness use vehicle-based feat..
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..