Heuristic architecture search using network morphism for Chest X-Ray classification
Küçük Resim Yok
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
CEUR-WS
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Nowadays, the demand for medical image computing is exceptionally high. This growth was mostly driven by the manual development of machine learning models, in particular neural networks. However, due to the constant evolution of domain requirements, manual model development has become insufficient. The present study proposes a heuristic architecture search that can be in an excellent service for the task of medical image classification. We implemented a novel approach called network morphism to the search algorithm. The proposed search method utilizes the enforced hill-climbing algorithm and functional-saving modifications. As a result of computational experiments, the search method found the optimal architecture in 28 GPU hours. The model formed by the found architecture achieved performance of 73.2% in validation accuracy and 84.5% in AUC on the validation dataset that is competitive to the state-of-the-art hand-crafted networks. Moreover, the proposed search method managed to find the architecture that contains four times fewer parameters. Besides, the model requires almost ten times less physical memory, which may indicate the practical usefulness of our method in medical image analysis. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). IntelITSIS-2020
Açıklama
1st International Workshop on Intelligent Information Technologies and Systems of Information Security, InteIITSIS 2020 -- 10 June 2020 through 12 June 2020 -- Khmelnytskyi -- 161234
Anahtar Kelimeler
Chest X-Ray, Heuristic search, Medical image classification, Network morphism, Neural architecture search
Kaynak
CEUR Workshop Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
2623
