Bilgisayar Mühendisliği Bölümü Makale Koleksiyonu
Recent Submissions
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Effects of Neighborhood-based Collaborative Filtering Parameters on Their Blockbuster Bias Performances
(Ağustos, 2)Collaborative filtering algorithms are efficient tools for providing recommendations with reasonable accuracy performances to individuals. However, the previous research has realized that these algorithms are undesirably ... -
Determination of Photonuclear Reaction Cross-Sections on Stable P-shell Nuclei by Using Deep Neural Networks
(Springer, 13 Mayıs 2)Photonuclear reactions are widely used in investigations of nuclear structure. Thus, the determination of the cross-sections are essential for the experimental studies. In the present work, (γ, n) photonuclear reaction ... -
Zero-shot learning via self-organizing maps
(Springer, 25.01.2023)Collecting-labeled images from all possible classes related to the task at hand is highly impractical and may even be impossible. At this point, Zero-Shot Learning (ZSL) can enable the classification of new test classes ... -
LVQ Treatment for Zero-Shot Learning
(Tubitak Academic Journals, 23.01.2023)In image classification, there are no labeled training instances for some classes, which are therefore called unseen classes or test classes. To classify these classes, zero-shot learning (ZSL) was developed, which typically ... -
Improving Brain Tumor Classification with Deep Learning Using Synthetic Data
(Tech Science Press, 2023)Deep learning (DL) techniques, which do not need complex pre-processing and feature analysis, are used in many areas of medicine and achieve promising results. On the other hand, in medical studies, a limited dataset ... -
A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves
(Tech Science Press, 2023)Parametric curves such as Bézier and B-splines, originally developed for the design of automobile bodies, are now also used in image processing and computer vision. For example, reconstructing an object shape in an image, ... -
Deep learning prediction of motor performance in stroke individuals using neuroimaging data
(Elsevier Science Direct, 2023)The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have ... -
A survey of smart home energy conservation techniques
(Elsevier, Mart, 2023)Smart homes are equipped with easy-to-interact interfaces, providing a more comfortable living environment and less energy consumption. There are currently satisfactory approaches proposed to deliver adequate comfort and ... -
Popularity bias in personality perspective: An analysis of how personality traits expose individuals to the unfair recommendation
(Wiley, Şubat, 202)Recommender systems are subject to well-known popularity bias issues, that is, they expose frequently rated items more in recommendation lists than less-rated ones. Such a problem could also have varying effects on users ... -
A novel classification‐based shilling attack detection approach for multi‐criteria recommender systems
(Wiley, Mayıs, 202)Recommender systems are emerging techniques guiding individuals with provided referrals by considering their past rating behaviors. By collecting multi-criteria preferences concentrating on distinguishing perspectives of ... -
Robustness of privacy-preserving collaborative recommenders against popularity bias problem
(PeerJ, Temmuz, 20)Recommender systems have become increasingly important in today’s digital age, but they are not without their challenges. One of the most significant challenges is that users are not always willing to share their preferences ... -
Aggregating user preferences in group recommender systems: A crowdsourcing approach
(Elsevier, 2022)We present that group recommendations are similar to crowdsourcing, where the responses of different crowd workers are aggregated in the absence of ground truth. With this in mind, we mimic the use of the EM algorithm as ... -
End to End Invoice Processing Application Based on Key Fields Extraction
(IEEE, 2022)In this paper, an automatic invoice processing system, which is in great demand among private and public companies, was proposed. The proposed system supports all invoice file types that can be submitted by companies. ... -
Exploring potential biases towards blockbuster items in ranking-based recommendations
(Springer, 2022)Popularity bias is defined as the intrinsic tendency of recommendation algorithms to feature popular items more than unpopular ones in the ranked lists lists they produced. When investigating the adverse effects of popularity ... -
Evaluating unfairness of popularity bias in recommender systems: A comprehensive user-centric analysis
(Elsevier, 2022)The popularity bias problem is one of the most prominent challenges of recommender systems, i.e., while a few heavily rated items receive much attention in presented recommendation lists, less popular ones are underrepresented ... -
IESR: Instant Energy Scheduling Recommendations for Cost Saving in Smart Homes
(IEEE, 10.05.2022)The exponential increase in energy demands continuously causes high price energy tariffs for domestic and commercial consumers. To overcome this problem, researchers strive to discover effective ways to reduce peak-hour ... -
A multiclass hybrid approach to estimating software vulnerability vectors and severity score
(Elsevier, 2021)Classifying detected software vulnerabilities is an important process. However, the metric values of security vectors are manually determined by humans, which takes time and may introduce errors stemming from human nature. ... -
Open Source Software Development Challenges: A Systematic Literature Review on GitHub
(IGI GLOBAL, 01.11.2021)GitHub is the most common code hosting and repository service for open-source software (OSS) projects. Thanks to the great variety of features, researchers benefit from GitHub to solve a wide range of OSS development ... -
New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems
(MDPI, 20.01.2021)Software collaboration platforms where millions of developers from diverse locations can contribute to the common open source projects have recently become popular. On these platforms, various information is obtained from ... -
Treating adverse effects of blockbuster bias on beyond-accuracy quality of personalized recommendations
(Elsevier, 2022)Collaborative filtering recommendation algorithms are vulnerable against the popularity bias, including the most popular items repeatedly into the produced ranked lists. However, the research on popularity bias focuses ...