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Toplam kayıt 86, listelenen: 61-70
Recommending Healthy Meal Plans by Optimising Nature-Inspired Many-Objective Diet Problem
(SAGE, 2021)
Healthy eating is an important issue affecting a large part of the world population, so human diets are
becoming increasingly popular, especially with the devastating consequences of Coronavirus Disease
(Covid-19). A ...
Controlling of Five Axis Manipulator with Turkish Voice Commands Using Microcontrollers
(Marmara Üniversitesi, 2018)
The interaction between human beings and machines has been increasing in conjunction with the development of computer technology.
Controlling a system with voice-based commands is one of the most popular applications in ...
Clustering Electricity Market Participants Via FRM Models
(IOS Press, 2020)
Collateral mechanism in the Electricity Market ensures the payments are executed on a timely manner; thus maintains
the continuous cash flow. In order to value collaterals, Takasbank, the authorized central settlement ...
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 ...
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 ...