Ara
Toplam kayıt 27, listelenen: 21-27
Deep Learning based Malware Detection for Android Systems: A Comparative Analysis
(Sveuciliste Josipa Jurja Strossmayera u Osijeku, 2023)
Nowadays, cyber attackers focus on Android, which is the most popular open-source operating system, as main target by applying some malicious software
(malware) to access users' private information, control the device, ...
A Novel Metaheuristic Based Method for Software Mutation Test Using the Discretized and Modified Forrest Optimization Algorithm
(Springer Lınk, 2023)
The number of detected bugs by software test data determines the efficacy of the test data. One of the most important topics
in software engineering is software mutation testing, which is used to evaluate the efficiency ...
Deep Learning With Class-Level Abstract Syntax Tree and Code Histories for Detecting Code Modification Requirements
(Elsevier, 2023)
Improving code quality is one of the most significant issues in the software industry. Deep learning
is an emerging area of research for detecting code smells and addressing refactoring requirements.
The aim of this study ...
Evolutionary Architecture Optimization for Retinal Vessel Segmentation
(IEEE, 2023)
Retinal vessel segmentation (RVS) is crucial
in medical image analysis as it helps identify and monitor
retinal diseases. Deep learning approaches have shown
promising results for RVS, but designing optimal neural
network ...
Radar Placement Optimization Based on Adaptive Multi-Objective Meta-Heuristics
(Elsevier, 2024)
Airspace surveillance is a significant issue for many countries to control and manage their airspace. The
number of radars used and their coverage rate are the main issues to consider in this case. Therefore, this
paper ...
Enhancing Resolution and Contrast in Fibre Bundle-Based Fluorescence Microscopy Using Generative Adversarial Network
(Wiley, 2024)
Fibre bundle (FB)-based endoscopes are indispensable in biology and medical
science due to their minimally invasive nature. However, resolution and contrast
for fluorescence imaging are limited due to characteristic ...
Sahand: A Software Fault-Prediction Method Using Autoencoder Neural Network and K-Means Algorithm
(Springer, 2024)
Software is playing a growing role in many safety-critical applications, and software systems dependability is a major concern. Predicting faulty modules of software before the testing phase is one method for enhancing ...