Accuracy on validation/hold-out dataset
Architecture name | Accuracy without segmentation | Accuracy post segmentation |
---|---|---|
ResNet18 | 0.52 | 0.62 |
ResNet34 | 0.56 | 0.65 |
ResNet50 | 0.61 | 0.66 |
MobileNetV1 | 0.60 | 0.66 |
MobileNetV2 | 0.62 | 0.69 |
Xception | 0.74 | 0.83 |
EfficientNetB0 | 0.76 | 0.89 |
The supplementary material for this article is available at: https://www.explorationpub.com/uploads/Article/file/1002158_sup_1.pdf.
AM: Conceptualization, Project administration, Investigation, Methodology, Supervision, Validation, Writing—review & editing. GB: Conceptualization, Data curation, Formal analysis, Investigation, Writing—review & editing, Writing—original draft. ST: Supervision. UB: Data curation, Formal analysis, Software. SW, UA, AKJ, VP, VN, NM, AT, JPA, SY, RK, AP, NP, and KP: Data curation, Investigation. All authors read and approved the submitted version.
The authors declare that they have no conflicts of interest.
The study was conducted after clearance from Institutional Ethics Committee (3296) and conducted in accordance with the guidelines of the Indian Council of Medical Research 2017. The research of this article meets the requirements of the Declaration of Helsinki.
Informed consent to participate in the study was obtained from all participants.
Informed consent to publication was obtained from relevant participants.
The datasets generated in this study are available on request to Abhishek Mahajan (drabhishek.mahajan@yahoo.in).
Not applicable.
© The Author(s) 2023.