Ara
Toplam kayıt 36, listelenen: 11-20
Multi-Objective Simulated Annealing for Hyper-Parameter Optimization in Convolutional Neural Networks
(PeerJ, Inc., 2021)
In this study, we model a CNN hyper-parameter optimization problem as a
bi-criteria optimization problem, where the first objective being the classification
accuracy and the second objective being the computational ...
Hyper-Parameter Selection in Convolutional Neural Networks Using Microcanonical Optimization Algorithm
(The Institute of Electrical and Electronics Engineers, 2020)
The success of Convolutional Neural Networks is highly dependent on the selected architecture
and the hyper-parameters. The need for the automatic design of the networks is especially important
for complex architectures ...
An Improved Bees Algorithm for Training Deep Recurrent Networks for Sentiment Classification
(MDPI, 2021)
Recurrent neural networks (RNNs) are powerful tools for learning information from
temporal sequences. Designing an optimum deep RNN is difficult due to configuration and training
issues, such as vanishing and exploding ...
GraphQL Sorgu Oluşturma Sürecinde Kullanılan Araç ve Yöntemlerin Analizi ve İyileştirilmesi
(Marmara University Journal of Science, 2021)
Günümüzde yaşanan teknolojik gelişmeler, İnternete bağlanan toplam cihaz tür ve sayısında büyük bir artışa yol açmıştır. Sunucu makineler daha fazla istek almaya başlamış hem ağ trafiği hem de sunucu yanıt süresi olumsuz ...
EEG Sinyallerinin Sınıflandırılmasında Evrimsel Öznitelik Seçim Metotlarının Kullanılması
(Marmara Üniversitesi, 2021)
Elektroensefalografi beyindeki elektriksel akımın ölçülmesi ile elde edilen sinyallerdir. Bu sinyallerin sınıflandırılması özellikle beyin sinyalleri ile ilgili rahatsızlıkların teşhis, tanı ve tedavisine katkı sağladığı ...
Iterative Enhanced Multivariance Products Representation for Effective Compression of Hyperspectral Images
(IEEE, November 2)
Effective compression of hyperspectral (HS) images
is essential due to their large data volume. Since these images are
high dimensional, processing them is also another challenging
issue. In this work, an efficient lossy ...
MS-TR: A Morphologically Enriched Sentiment Treebank and Recursive Deep Models for Compositional Semantics in Turkish
(Taylor & Francis, 2021)
Recursive Deep Models have been used as powerful models to learn
compositional representations of text for many natural language processing tasks.
However, they require structured input (i.e. sentiment treebank) to encode ...
AT-ODTSA: a Dataset of Arabic Tweets for Open Domain Targeted Sentiment Analysis
(University of Bahrain, 2022)
In the field of sentiment analysis, most of research has conducted experiments on datasets collected from Twitter for
manipulating a specific language. Little number of datasets has been collected for detecting sentiments ...
Experimental Evaluation of Meta-Heuristics for Multi-Objective Capacitated Multiple Allocation Hub Location Problem
(Elsevier, 2022)
Multi-objective capacitated multiple allocation hub location problem (MOCMAHLP) is a variation of classic
hub location problem, which deals with network design, considering both the number and the location
of the hubs ...
The Best Approximation of Generalized Fuzzy Numbers Based on Scaled Metric
(Hindawi Limited., 2022)
The ongoing study has been vehemently allocated to propound an ameliorated α-weighted generalized approximation of an arbitrary fuzzy number. This method sets out to lessen the distance between the original fuzzy set and ...