Heuristic Architecture Search Using Network Morphism for Chest X-Ray Classification
Küçük Resim Yok
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Rwth Aachen
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.
Açıklama
1st International Workshop on Intelligent Information Technologies and Systems of Information Security (IntelITSIS) -- JUN 10-12, 2020 -- ELECTR NETWORK
Anahtar Kelimeler
heuristic search, neural architecture search, network morphism, medical image classification, Chest X-Ray
Kaynak
Proceedings of the 1st International Workshop On Intelligent Information Technologies & Systems of Information Security (Intelitsis 2020), Vol 1
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
2623
