Custom Deep Neural Network for 3D Covid Chest CT-scan Classification
Not on the map. Why?
Abstract (arXiv)
3D CT-scan base on chest is one of the controversial topisc of the researcher nowadays. There are many tasks to diagnose the disease through CT-scan images, include Covid19. In this paper, we propose a method that custom and combine Deep Neural Network to classify the series of 3D CT-scans chest images. In our methods, we experiment with 2 backbones is DenseNet 121 and ResNet 101. In this proposal, we separate the experiment into 2 tasks, one is for 2 backbones combination of ResNet and DenseNet, one is for DenseNet backbones combination.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 7 references that are in the map. First posted on arXiv 3 Jul 2021.
Builds on
5 of 7 references.
References · 5
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2016Densely Connected Convolutional Networkscited by 6,691
- 2020Deep Transparent Prediction through Latent Representation Analysiscited by 72
- 2021MIA-COV19D: COVID-19 Detection through 3-D Chest CT Image Analysiscited by 72
- 2019Macro F1 and Macro F1cited by 70
Built on by
Citing papers per year: 2021: 1.
1 paper.