V
Volkan Atalay
Researcher at Middle East Technical University
Publications - 80
Citations - 2304
Volkan Atalay is an academic researcher from Middle East Technical University. The author has contributed to research in topics: Deep learning & Computer science. The author has an hindex of 20, co-authored 76 publications receiving 1629 citations. Previous affiliations of Volkan Atalay include Virginia Tech & Paris Descartes University.
Papers
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Journal ArticleDOI
Projection based method for segmentation of human face and its evaluation
TL;DR: This work detects facial features and circumscribe each facial feature with the smallest rectangle possible by using vertical and horizontal gray value projections of pixels.
Journal ArticleDOI
ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature.
Alperen Dalkiran,Alperen Dalkiran,Ahmet Sureyya Rifaioglu,Maria Jesus Martin,Rengul Cetin-Atalay,Volkan Atalay,Tunca Doğan,Tunca Doğan +7 more
TL;DR: ECPred is presented both as a stand-alone and a web based tool to provide probabilistic enzymatic function predictions (at all five levels of EC) for uncharacterized protein sequences.
Proceedings ArticleDOI
Feature extraction and classification of blood cells for an automated differential blood count system
TL;DR: Classification of blood cells using various approaches including neural network based classifiers and support vector machine are presented together with the features used in the classification.
Journal ArticleDOI
The random neural network model for texture generation
TL;DR: Numerical iterations of the field equations of the random neural network model, starting with a randomly generated gray-level image, are shown to produce textures having different desirable features such as granularity, inclination, and randomness.
Journal ArticleDOI
DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks
Ahmet Sureyya Rifaioglu,Tunca Doğan,Tunca Doğan,Maria Jesus Martin,Rengul Cetin-Atalay,Volkan Atalay +5 more
TL;DR: DEEPred, a hierarchical stack of multi-task feed-forward deep neural networks, is proposed as a solution to Gene Ontology based protein function prediction and the neural network architecture of DEEPred can also be applied to the prediction of the other types of ontological associations.