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Neural Architecture Search Using Metaheuristics for Automated Cell Segmentation
(Springer, 2023)
Deep neural networks give successful results for segmentation of medical images. The need for optimizing many hyper-parameters
presents itself as a significant limitation hampering the effectiveness of
deep neural network ...
Novel Surrogate Measures Based on a Similarity Network for Neural Architecture Search
(IEEE, 2023)
We propose two novel surrogate measures to predict the validation accuracy of the classification
produced by a given neural architecture, thus eliminating the need to train it, in order to speed up neural
architecture ...
BaDENAS: Retina Damar Segmentasyonu için Bayes Tabanlı Sinir Mimarisi Arama
(IEEE, 2023)
Retinal damar segmentasyonu, retinal görüntülerin analizi için önemli bir görevdir ve göz hastalıklarının teşhisinde ve tedavisinde kullanılan etkili bir araçtır. Damar segmentasyonunu otomatik hale getiren U-Net gibi derin ...
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 ...
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 ...