Search Results - "Karaçalı, Bilge"
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Time-resolved EEG signal analysis for motor imagery activity recognition
Published in Biomedical signal processing and control (01-09-2023)“…•Two novel approaches are proposed exploiting the activity-specific temporal and spatio-spectral organization of EEG signals for motor imagery recognition.•The…”
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2
Quasi‐supervised Strategies for Compound‐protein Interaction Prediction
Published in Molecular informatics (01-04-2022)“…In‐silico compound‐protein interaction prediction addresses prioritization of drug candidates for experimental biochemical validation because the wet‐lab…”
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Evaluation of synchronization measures for capturing the lagged synchronization between EEG channels: A cognitive task recognition approach
Published in Computers in biology and medicine (01-11-2019)“…During cognitive, perceptual and sensory tasks, connectivity profile changes across different regions of the brain. Variations of such connectivity patterns…”
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Quasi-supervised learning for biomedical data analysis
Published in Pattern recognition (01-10-2010)“…We present a novel formulation for pattern recognition in biomedical data. We adopt a binary recognition scenario where a control dataset contains samples of…”
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5
An efficient algorithm for large-scale quasi-supervised learning
Published in Pattern analysis and applications : PAA (01-05-2016)“…We present a novel formulation for quasi-supervised learning that extends the learning paradigm to large datasets. Quasi-supervised learning computes the…”
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6
On the characterization of cognitive tasks using activity-specific short-lived synchronization between electroencephalography channels
Published in Neural networks (01-11-2021)“…Accurate characterization of brain activity during a cognitive task is challenging due to the dynamically changing and the complex nature of the brain. The…”
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7
Reconstructing discontinuous surfaces from a given gradient field using partial integrability
Published in Computer vision and image understanding (01-10-2003)“…This paper describes an adaptive surface reconstruction method from a given gradient field that allows discontinuities in the solution. We first formalize a…”
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8
Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers
Published in BMC medical imaging (06-09-2007)“…Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an…”
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9
Information theoretic deformable registration using local image information
Published in International journal of computer vision (01-05-2007)“…We present a deformable registration algorithm for multi-modality images based on information theoretic similarity measures at the scale of individual image…”
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10
Identification and visualization of cell subgroups in uncompensated flow cytometry data
Published in Chemometrics and intelligent laboratory systems (15-01-2020)“…We propose a new method for identification and visualization of cell-sub groups in uncompensated multi-color flow cytometry data. The method combines…”
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11
Hierarchical Motif Vectors for Prediction of Functional Sites in Amino Acid Sequences Using Quasi-Supervised Learning
Published in IEEE/ACM transactions on computational biology and bioinformatics (01-09-2012)“…We propose hierarchical motif vectors to represent local amino acid sequence configurations for predicting the functional attributes of amino acid sites on a…”
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12
Automatic identification of highly conserved family regions and relationships in genome wide datasets including remote protein sequences
Published in PloS one (12-09-2013)“…Identifying shared sequence segments along amino acid sequences generally requires a collection of closely related proteins, most often curated manually from…”
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13
Morphological classification of brains via high-dimensional shape transformations and machine learning methods
Published in NeuroImage (Orlando, Fla.) (2004)“…A high-dimensional shape transformation posed in a mass-preserving framework is used as a morphological signature of a brain image. Population differences with…”
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14
A computational analysis of Turkish makam music based on a probabilistic characterization of segmented phrases
Published in Journal of mathematics and music (Society for Mathematics and Computation in Music) (02-01-2015)“…This study targets automatic analysis of Turkish makam music pieces on the phrase level. While makam is most simply defined as an organization of melodic…”
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15
Fisher’s Linear Discriminant Analysis Based Prediction using Transient Features of Seismic Events in Coal Mines
Published in Annals of Computer Science and Information Systems (03-11-2016)Get full text
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16
Automated detection of regions of interest for tissue microarray experiments: an image texture analysis
Published in BMC medical imaging (09-03-2007)“…Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue…”
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Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets
Published in BMC bioinformatics (26-10-2007)“…Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression…”
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18
Usul and Makam driven automatic melodic segmentation for Turkish music
Published in Journal of new music research (02-10-2014)“…Automatic melodic segmentation is a topic studied extensively, aiming at developing systems that perform grouping of musical events. Here, we consider the…”
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The prognostic value of tumor-stroma proportion in laryngeal squamous cell carcinoma
Published in Türk patoloji dergisi (2013)“…Tumor-stroma proportion of tumor has been presented as a prognostic factor in some types of adenocarcinomas, but there is no information about squamous cell…”
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A comparative analysis of structural risk minimization by support vector machines and nearest neighbor rule
Published in Pattern recognition letters (2004)“…Support vector machines (SVMs) are by far the most sophisticated and powerful classifiers available today. However, this robustness and novelty in approach…”
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