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Toplam kayıt 17, listelenen: 11-17
Hücre Canlılığı Tespitinde Yapay Öğrenme Yaklaşımları
(IEEE, 2023)
Hücre canlılığı, kök hücre tedavileri, kanser tedavileri, estetik ve kozmetik gibi klinik araştırmalarda önemli yer tutmaktadır. Doğru tedavi ve yaklaşımın uygulanabilmesi için alınan örnekteki toplam hücre canlılık oranı ...
What to predict from Twitter Data?
(IEEE, 2023)
In the last decade, Twitter data has become one
of the most valuable research sources for many areas including
health, marketing, security, and politics. Researchers prefer
Twitter data since it is completely public and ...
A Unified Framework for Multi-Language Sentiment Analysis
(IEEE, 2023)
The unified framework for multi-language
sentiment analysis is a vital aspect of understanding customer
opinions, emotions, and feedback. This paper presents a unified
framework to increase the performance of the ...
Classification of Fruit Images as Fresh and Rotten Using Convolutional Neural Networks
(IEEE, 2023)
Many fruits are produced all over the world, and the fruits produced are sent abroad and sold in a relatively short time in many countries. During the period between collection and sale, the fruits may undergo various types ...
Deep Learning With Class-Level Abstract Syntax Tree and Code Histories for Detecting Code Modification Requirements
(Elsevier, 2023)
Improving code quality is one of the most significant issues in the software industry. Deep learning
is an emerging area of research for detecting code smells and addressing refactoring requirements.
The aim of this study ...
Triplet MAML for Few-shot Classification Problems
(Springer, 2023)
In this study, we propose a TripletMAML algorithm as an extension to Model-Agnostic Meta-Learning (MAML) which is the most widely-used optimization-based meta-learning algorithm. We approach MAML from a metric-learning ...
Evolutionary Architecture Optimization for Retinal Vessel Segmentation
(IEEE, 2023)
Retinal vessel segmentation (RVS) is crucial
in medical image analysis as it helps identify and monitor
retinal diseases. Deep learning approaches have shown
promising results for RVS, but designing optimal neural
network ...