Yayıncı "Springer" Bilgisayar Mühendisliği Bölümü için listeleme
Toplam kayıt 13, listelenen: 1-13
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Bi-criteria Simulated Annealing for the Curriculum-based Course Timetabling Problem With Robustness Approximation
(Springer, 2022)In the process of developing a university’s weekly course timetable, changes in the data, such as the available time periods of professors or rooms, render the timetable infeasible, requiring the administrators to repair ... -
A Comparison of Different Loss Computations in Siamese Networks for Authorship Verification
(Springer, 2023)In this study, we consider the author verification problem as a binary classification problem where the aim is to identify whether the two inputs belong to the same author or not. For this task, we have used several ... -
Detecting SQL Injection Attacks by Binary Gray Wolf Optimizer and Machine Learning Algorithms
(Springer, 2024)SQL injection is one of the important security issues in web applications because it allows an attacker to interact with the application’s database. SQL injection attacks can be detected using machine learning algorithms. ... -
A Fast Algorithm for Hunting State-Backed Twitter Trolls
(Springer, 2022)In recent years, state-backed troll accounts have been adopted extensively by many political parties, organizations, and governments to negatively influence political systems, persecute perceived opponents, and exacerbate ... -
Fast Iris Segmentation Algorithm for Visible Wavelength Images Based on Multi-color Space
(Springer, 2020)Iris recognition for eye images acquired in visible wavelength is receiving increasing attention. In visible wavelength environments, there are many factors that may cover or affect the iris region which makes the iris ... -
Maximizing Coverage and Maintaining Connectivity in WSN and Decentralized Iot: An Efficient Metaheuristic-Based Method for Environment-Aware Node Deployment
(Springer, 2022)The node deployment problem is a non-deterministic polynomial time (NP-hard). This study proposes a new and efficient method to solve this problem without the need for predefined circumstances about the environments ... -
Metaheuristic Algorithms in IoT: Optimized Edge Node Localization
(Springer, 2022)In this study, a new hybrid method is proposed by using the advantages of Grey Wolf Optimizer (GWO) and Moth-Flame Optimization (MFO) algorithms. The proposed hybrid metaheuristic algorithm tries to find the near-optimal ... -
Neural Architecture Search Using Metaheuristics for Automated Cell Segmentation
(Springer, 2023)Deep neural networks give successful results for segmentation of medical images. The need for optimizing many hyper-parameters presents itself as a significant limitation hampering the effectiveness of deep neural network ... -
A New Prediction-Based Algorithm for Dynamic Multi-objective Optimization Problems
(Springer, 2023)The mechanism for reacting to the changes in an environ- ment when detected is the key issue that distinguishes various algorithms proposed for dynamic multi-objective optimization problems (DMOPs). The severity of ... -
On a Class of Semicommutative Modules
(Springer, 2009)Let R be a ring with identity,M a right R-module and S = EndR(M). In this note, we introduce S-semicommutative, S-Baer, S-q.-Baer and S-p.q.-Baer modules. We study the relations between these classes of modules. Also we ... -
Prediction of the Remaining Useful Life of Engines for Remanufacturing Using a Semi-supervised Deep Learning Model Trained by the Bees Algorithm
(Springer, 2023)Smart and sustainable manufacturing is important for enterprises to handle global challenges [1]. Products, systems, and components are reused, remanufactured, and recycled instead of being disposed of in landfills, which ... -
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 ... -
Triplet MAML for Few-shot Classification Problems
(Springer, 2023)In this study, we propose a TripletMAML algorithm as an extension to Model-Agnostic Meta-Learning (MAML) which is the most widely-used optimization-based meta-learning algorithm. We approach MAML from a metric-learning ...