Ara
Toplam kayıt 6, listelenen: 1-6
The analysis of text categorization represented with word embeddings using homogeneous classifiers
(Institute of Electrical and Electronics Engineers Inc., 2019)
Text data mining is the process of extracting and analyzing valuable information from text. A text data mining process generally consists of lexical and syntax analysis of input text data, the removal of non-informative ...
Deep learning for inverse problems in imaging
(IEEE, 2019)
Inverse problems have been widely studied in image processing, with applications in areas such as image denoising, blind/non-blind deblurring, super-resolution and compressive sensing. Lately deep learning techniques and ...
A model based on random walk with restart to predict circRNA-disease associations on heterogeneous network
(Association for Computing Machinery, 2019)
Recent studies show that circRNAs have critical roles in many biological processes. Knowing the associations between circRNAs and diseases may contribute to the understanding of the mechanism of circRNAs and to the diagnostic ...
Uzaktan algılanan görüntülerde bina yoğunluğu kestirimi için derin öğrenme
(Institute of Electrical and Electronics Engineers Inc., 2019)
Bu bildiri, derin öğrenme yöntemleri uygulayarak uzaktan algılamalı optik görüntülerde bina yoğunluğunun noktasal olarak kestirilmesi ile ilgilidir. Bu çalışma kapsamında, evrişimsel sinir ağına (ESA) dayalı derin öğrenme ...
The evaluation of word embedding models and deep learning algorithms for Turkish text classification
(IEEE (Institute of Electrical and Electronics Engineers), 2019)
The use of word embedding models and deep learning algorithms are currently the most common and popular trends to enhance the overall performance of a text classification/categorization system. Word embedding models are ...
Effective induction of gene regulatory networks using a novel recommendation method
(Inderscience Enterprises Ltd., 2019)
In this paper, we introduce a method based on recommendation systems to predict the structure of Gene Regulatory Networks (GRNs) making use of data from multiple sources. Our method is based on collaborative filtering ...