Browsing by Author "Koç, Aykut"
Now showing items 1-20 of 26
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Discrete linear canonical transform based on hyperdifferential operators
(IEEE, 2019-05)Linear canonical transforms (LCTs) are of importance in many areas of science and engineering with many applications. Therefore, a satisfactory discrete implementation is of considerable interest. Although there are methods ... -
Discrete scaling based on operator theory
(Elsevier, 2020-11-04)Signal scaling is a fundamental operation of practical importance in which a signal is made wider or narrower along the coordinate direction(s). Scaling, also referred to as magnification or zooming, is complicated for ... -
The effect of gender bias on hate speech detection
(Springer, 2022-10-08)Hate speech against individuals or communities with different backgrounds is a major problem in online social networks. The domain of hate speech has spread to various topics, including race, religion, and gender. Although ... -
Factorized sensitivity estimation for artifact suppression in phase‐cycled bSSFP MRI
(Wiley, 2020)Objective: Balanced steady‐state free precession (bSSFP) imaging suffers from banding artifacts in the presence of magnetic field inhomogeneity. The purpose of this study is to identify an efficient strategy to reconstruct ... -
Feedforward neural network based case prediction in Turkish higher courts
(2022-08-29)Thanks to natural language processing (NLP) methods, legal texts can be processed by computers and decision prediction applications can be developed in the legal tech field. Increase in the available data sources in the ... -
Fractional fourier transform in time series prediction
(IEEE, 2022-12-09)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 ... -
Fractional fourier transform meets transformer encoder
(Institute of Electrical and Electronics Engineers, 2022-10-28)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 ... -
Gender bias in legal corpora and debiasing it
(Cambridge University Press, 2022-03-30)Word embeddings have become important building blocks that are used profoundly in natural language processing (NLP). Despite their several advantages, word embeddings can unintentionally accommodate some gender- and ... -
Graph signal processing: Vertex multiplication
(IEEE, 2021-06-03)On the Euclidean domains of classical signal processing, linking of signal samples to underlying coordinate structures is straightforward. While graph adjacency matrices totally define the quantitative associations among ... -
Imparting interpretability to word embeddings while preserving semantic structure
(Cambridge University Press, 2020)As a ubiquitous method in natural language processing, word embeddings are extensively employed to map semantic properties of words into a dense vector representation. They capture semantic and syntactic relations among ... -
Learning interpretable word embeddings via bidirectional alignment of dimensions with semantic concepts
(Elsevier Ltd, 2022-03-22)We propose bidirectional imparting or BiImp, a generalized method for aligning embedding dimensions with concepts during the embedding learning phase. While preserving the semantic structure of the embedding space, BiImp ... -
Multi-label sentiment analysis on 100 languages with dynamic weighting for label imbalance
(Institute of Electrical and Electronics Engineers, 2021-07-19)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 ... -
Multivariate time series imputation with transformers
(IEEE, 2022-11-25)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 ... -
Named-entity recognition in Turkish legal texts
(Cambridge University Press, 2022-07-11)Natural language processing (NLP) technologies and applications in legal text processing are gaining momentum. Being one of the most prominent tasks in NLP, named-entity recognition (NER) can substantiate a great convenience ... -
Natural language processing in law: Prediction of outcomes in the higher courts of Turkey
(Elsevier Ltd, 2021-09)Natural language processing (NLP) based approaches have recently received attention for legal systems of several countries. It is of interest to study the wide variety of legal systems that have so far not received any ... -
Operator theory-based computation of linear canonical transforms
(Elsevier, 2021-08-12)Linear canonical transforms (LCTs) are extensively used in many areas of science and engineering with many applications, which requires a satisfactory discrete implementation. Recently, hyperdifferential operators have ... -
Operator theory-based discrete fractional Fourier transform
(Springer, 2019)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, ... -
Optimal fractional fourier filtering for graph signals
(IEEE, 2021-05-19)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. ... -
Predicting outcomes of the court of cassation of Turkey with recurrent neural networks
(IEEE, 2022-08-29)Natural Language Processing (NLP) based approaches have recently become very popular for studies in legal domain. In this work, the outcomes of the cases of the Court of Cassation of Turkey were predicted with the use of ... -
Relationship between the beam propagation method and linear canonical and fractional Fourier transforms
(Optica, 2022)The beam propagation method (BPM) can be viewed as a chain of alternating convolutions and multiplications, as filtering operations alternately in the space and frequency domains or as multiplication operations sandwiched ...
