Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Aykut Koc"'
Autor:
Furkan Sahinuc, Aykut Koc
Publikováno v:
IEEE Signal Processing Letters
Utilizing signal processing tools in deep learning models has been drawing increasing attention. Fourier transform (FT), one of the most popular signal processing tools, is employed in many deep learning models. Transformer-based sequential input pro
Autor:
Emirhan Koc, Aykut Koc
Publikováno v:
IEEE Signal Processing Letters
Several signal processing tools are integrated into machine learning models for performance and computational cost improvements. Fourier transform (FT) and its variants, which are powerful tools for spectral analysis, are employed in the prediction o
Publikováno v:
IEEE Signal Processing Letters
Processing time series with missing segments is a fundamental challenge that puts obstacles to advanced analysis in various disciplines such as engineering, medicine, and economics. One of the remedies is imputation to fill the missing values based o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b820a06ef9fd620ba8a9836f7eb58c7
https://hdl.handle.net/11693/111208
https://hdl.handle.net/11693/111208
Publikováno v:
Signal Processing and Communications Applications Conference (SIU)
Conference Name: 2022 30th Signal Processing and Communications Applications Conference (SIU) Date of Conference: 15-18 May 2022 Natural Language Processing (NLP) based approaches have recently become very popular for studies in legal domain. In this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fdcdb55840da02c2023a4b62fe49941
https://hdl.handle.net/11693/111316
https://hdl.handle.net/11693/111316
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing
Diachronic study of the evolution of languages is of importance in natural language processing (NLP). Recent years have witnessed a surge of computational approaches for the detection and characterization of lexical semantic change (LSC) due to the a
Publikováno v:
IEEE Transactions on Signal Processing
Graph signal processing has recently received considerable attention. Several concepts, tools, and applications in signal processing such as filtering, transforming, and sampling have been extended to graph signal processing. One such extension is th
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems
We investigate cross-lingual sentiment analysis, which has attracted significant attention due to its applications in various areas including market research, politics and social sciences. In particular, we introduce a sentiment analysis framework in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::119bee6fa9b0dc258306dd849344ddf2
https://hdl.handle.net/11693/77683
https://hdl.handle.net/11693/77683
Autor:
Aykut Koc, Nurullah Sevim
Publikováno v:
SIU
Investigating gender bias in Natural Language Processing has recently gained importance due to the negative consequences of a possible sexist approach. Especially by examining such biases in English word embeddings in various contexts, many studies h
Publikováno v:
SIU
Microblogs are short and irregular texts in which people express their opinions in social media. While classification of social media microblog texts according to their topics constitutes a semantic substructure, it helps implementation of various ap
Autor:
Aykut Koc
Publikováno v:
Signal, Image and Video Processing
The fractional Fourier transform is of importance in several areas of signal processing with many applications including optical signal processing. Deploying it in practical applications requires discrete implementations, and therefore defining a dis