Bildiri Koleksiyonu | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Güncel Gönderiler
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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 ... -
Forecasting and analysis of energy consumption and waste generation in Antalya with SVR
(IEEE, 2023-12-24)Antalya, a rapidly expanding coastal city in Türkiye, has experienced significant changes due to urbanization and increasing tourism activities. Comprehending tourism trends is crucial for the city's sustainable development ... -
Application of ChatGPT in the tourism domain: potential structures and challenges
(IEEE, 2023-12-23)The tourism industry stands out as a sector where effective customer communication significantly influences sales and customer satisfaction. The recent shift from traditional natural language processing methodologies to ... -
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 ... -
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, ... -
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 ... -
Auto Train Brain increases the variance of the gamma band sample entropy in the left hemisphere in dyslexia: a pilot study
(Springer Science and Business Media Deutschland GmbH, 2023)Auto Train Brain is a mobile app that improves reading speed and reading comprehension in dyslexia. The efficacy of Auto Train Brain was proven with a clinical trial. We have analyzed the long-term training effects of the ... -
Convolutional neural network (CNN) algorithm based facial emotion recognition (FER) system for FER-2013 dataset
(IEEE, 2022-11-18)Facial expression recognition (FER) is the key to understanding human emotions and feelings. It is an active area of research since human thoughts can be collected, processed, and used in customer satisfaction, politics, ... -
Analysis of single image super resolution models
(IEEE, 2022-11-18)Image Super-Resolution (SR) is a set of image processing techniques which improve the resolution of images and videos. Deep learning approaches have made remarkable improvement in image super-resolution in recent years. ... -
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, ... -
El yazısı rakam sınıflandırması için gözetimsiz benzerlik tabanlı evrişimler
(Institute of Electrical and Electronics Engineers Inc., 2022)Effective training of filters in Convolutional Neural Networks (CNN) ensures their success. In order to achieve good classification results in CNNs, filters must be carefully initialized, trained and fine-tuned. We propose ... -
Comparison of choreography vs orchestration based Saga patterns in microservices
(Institute of Electrical and Electronics Engineers Inc., 2022)Microservice Architecture (MSA) is a design and architecture pattern created to deal with the challenges of conventional software programs in terms of stream processing, highly available flexibility, and infrastructural ... -
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 ...