Objective To design an efficient algorithm for detection of anomaly in 5G network and perform efficient forecast model. Abstract Accurate and autonomous traffic forecasting is essential for many traffic ma..
Abstract: MOBILE devices, including smart phones, are being used by billions of people all around the world. This creates the opportunity to design a wide variety of mobile image applications, Among many imaging applications, healthcare applications have drawn a lot of attentions..
AF-DCGAN: Amplitude Feature Deep Convolutional GAN for Fingerprint Construction in Indoor Localization Systems
Technology: DEEP LEARNING / GAN ..
Aim: Aim of this project is to build a surveillance system for home to identify the presence of human and notify to the owner of house.Abstract: Internet of Things (IoT) is an emerging technology which is making our world smarter. The dev..
Abstract: While the concept of ultra-dense small cell networks (SCNs) has brought a number of significant opportunities for the telecommunication industry, it has also introduced a major challenge for researchers, who must develop techniques to reduce the sharp i..
Abstract SHIP detection in remote-sensing images is important in both civilian and military applications, such as traffic dynamic monitoring, fishery management, security threats uncovering, illegal activities uncovering. the framework is designed to access the fin..
AREA DETERMINATION OF DIABETIC FOOT ULCER IMAGES USING A CASCADED TWO-STAGE SVM BASED CLASSIFICATION
Aim: The mainstay of the project is to determine the wound boundary on a foot ulcer image. Introduction: Doctors base their wound assessment primarily on visual examination and manual measurements per..
Brain tumor segmentation and its area calculation in brain MR images using K-mean clustering and Fuzzy C-mean
Abstract: 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 brain tumor automatic identification is of great interest. In Order to detect the brain tumor of a patient we consider the data of pati..
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..
Abstract: Since texts in traffic signs have precise and rich semantic information related to traffic condition, text-based traffic sign detection plays an important role in the autonomous driving and auxiliary driving of Intelligent Transportation System, just as traffic congestion det..
Domain: Machine Learning ..
Cost-Effective Vehicle Type Recognition in Surveillance Images with Deep Active Learning and Web Data
Abstract: With the rapid development of Intelligent Transportation System (ITS) technologies in recent years, vehicle type recognition (VTR) has been widely applied as a low-cost technology in tolls, transportation statistics, security and crime prevention issues. The early techniques for VTR mainl..
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..