Başlık için Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering listeleme
Toplam kayıt 22, listelenen: 11-22
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Graph convolutional network based virus-human protein-protein interaction prediction for novel viruses
(Elsevier Ltd, 2022-08-13)Computational identification of human-virus protein-protein interactions (PHIs) is a worthwhile step towards understanding infection mechanisms. Analysis of the PHI networks is important for the determination of path-ogenic ... -
Hotel sales forecasting with LSTM and N-BEATS
(IEEE, 2023-09-15)Time series forecasting aims to model the change in data points over time. It is applicable in many areas, such as energy consumption, solid waste generation, economic indicators (inflation, currency), global warming (heat, ... -
Implementing lightweight, dynamic hierarchical key assignment scheme for cloud computing
(IEEE, 2024-03-25)In this paper, we propose the implementation and adaptation of a hierarchical key assignment scheme (HKAS) previously developed in our research to improve access control in cloud computing environments. The secret keys ... -
ISIKSumm at BioLaySumm task 1: BART-based summarization system enhanced with Bio-entity labels
(Association for Computational Linguistics (ACL), 2023-07-13)Communicating scientific research to the general public is an essential yet challenging task. Lay summaries, which provide a simplified version of research findings, can bridge the gap between scientific knowledge and ... -
Leveraging transformer-based language models for enhanced service insight in tourism
(IEEE, 2023-12-22)Customer feedback is a valuable resource for enhancing customer experience and identifying areas that require improvement. Utilizing user insights allows a tourism company to identify and address problematic points in its ... -
Machine learning-based model categorization using textual and structural features
(Springer Science and Business Media Deutschland GmbH, 2022-09-08)Model Driven Engineering (MDE), where models are the core elements in the entire life cycle from the specification to maintenance phases, is one of the promising techniques to provide abstraction and automation. However, ... -
A novel similarity based unsupervised technique for training convolutional filters
(IEEE, 2023-05-17)Achieving satisfactory results with Convolutional Neural Networks (CNNs) depends on how effectively the filters are trained. Conventionally, an appropriate number of filters is carefully selected, the filters are initialized ... -
A short proof of the size of edge-extremal chordal graphs
(Mahmut Akyiğit, 2022-08-30)Blair et. al. [3] have recently determined the maximum number of edges of a chordal graph with a maximum degree less than d and the matching number at most ? by exhibiting a family of chordal graphs achieving this bound. ... -
TENET: a new hybrid network architecture for adversarial defense
(Springer Science and Business Media Deutschland GmbH, 2023-08)Deep neural network (DNN) models are widely renowned for their resistance to random perturbations. However, researchers have found out that these models are indeed extremely vulnerable to deliberately crafted and seemingly ... -
TUR2SQL: A cross-domain Turkish dataset for Text-to-SQL
(IEEE, 2023-09-15)The field of converting natural language into corresponding SQL queries using deep learning techniques has attracted significant attention in recent years. While existing Text-to-SQL datasets primarily focus on English and ... -
Türkmed: Türkçe metinlerin konusal / duygusal sınıflandırması ve kelimelerin anlam bulanıklığını gidermek için difüzyon ve Seq2seq-füzyon algoritmalarını içeren özgün makine öğrenmesi ve derin öğrenme yöntemlerinin geliştirilmesi
(Tübitak, 2024-01-29)Bu proje teklifinde sunulan projemiz 3 ana hedeften oluşmaktadır. Bunlar: 1. Türkçe eş sesli kelimelerin bulundukları bağlamdaki doğru anlamlarının tespit edilmesi, 2. Türkçe uzun ve kısa metinlerin konu ve duygu bazlı ... -
Unreasonable effectiveness of last hidden layer activations for adversarial robustness
(Institute of Electrical and Electronics Engineers Inc., 2022)In standard Deep Neural Network (DNN) based classifiers, the general convention is to omit the activation function in the last (output) layer and directly apply the softmax function on the logits to get the probability ...