Improving Dehazing Results for Different Weather Conditions using Guided Multi-Model Adaptive Network (GMAN) and Cross-Entropy Deep Learning Neural Network (CE-DLNN)
Online National Citizen's ID Renewal System
Deep Learning MRI Analysis for Automated Knee Injury Diagnosis
Gas Leakage Detection using Convolution Neural Networks
Deep Learning for Enhancing Internet of Things: A Comprehensive Survey
Efficient Agent Based Priority Scheduling and LoadBalancing Using Fuzzy Logic in Grid Computing
A Survey of Various Task Scheduling Algorithms In Cloud Computing
Integrated Atlas Based Localisation Features in Lungs Images
A Computational Intelligence Technique for Effective Medical Diagnosis Using Decision Tree Algorithm
A Viable Solution to Prevent SQL Injection Attack Using SQL Injection
Medical image processing is used for analyzing medical images, quantitatively. There exists many medical image modalities like Magnetic Resonance Images (MRI), Computed Tomography (CT), Ultrasound (US), etc. Among them, Ultrasound is a conventional device still practiced in medical field. The Ultrasonic image obtained from US devices is often degraded by the speckle noise. Speckle noise degrades the original image quality; so it needs an efficient denoising for despecklng it. Hence, the authors have found a non-linear denoising filter to remove the speckle noise effectively. In this paper, adaptive fuzzy based non- linear filter has been applied to various ultrasound images which got corrupted with the speckle noise. Experimental results are achieved by calculating the performance metrics such as Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Signal-to-Noise Ratio (SNR), that shows the workability of the proposed approach. These results are also compared with other median based denoising filters by analytical proportion.
Location based query services are popular, and have a great demand. The authors have proposed a framework using Anonymous query processing to find the exact location of the places. Previous network database requires no specified storage or functions. In this paper, an anonymous query processing is utilized, where the user can send a query and get the results without leaking their identity to the server. By this anonymous technique, the user can identify the locations very easily using two types of query. This technique has achieved better performance.
Phishing attacks cause companies and individuals huge economic as well as intangible damages. Phishing attacks employ a litany of attack vectors. To deal with such attacks, counter work needs to be done in several areas. In this paper, the authors have presented a survey of literature on phishing detection and the current trends in phishing. The authors have also mentioned that phishing detection can be classified into three main categories namely, disallowing attacks to reach the users, user training, and more useful user interfaces. The goal of this paper is to cover all important aspects involved in phishing detection as compared to existing surveys on phishing detection that have focused on individual aspects. There has been a continuous increase in phishing attacks, with a sharp rise in Spear phishing and attacks over Social Media.
Internet of Things (IoT) is a system of connected physical objects that are accessible through internet. Values that are allocated to an IP address have the potential to collect and fetch the data over a network, without manual involvement. With continuous developments in Internet of Things (IoT) applications, the conventional computing is facing severe challenges such as high latency, decreased efficiency, long transmission times and increased power consumption. In order to meet these requirements, the data computation and service supply are moved from cloud to edge known as Edge Analytics. An Edge Analytics application utilizes the handling energy of IoT gadgets to channel, pre-process, and total the IoT information. It utilizes the power and adaptability of Cloud administrations to run complex examination on the information, that refers to the enabling technologies allowing computation to be performed at the edge of the network. The term “edge” refers to any computing and network resources along the path between data sources and cloud data centers.