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CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans.

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Improved Explainability of Capsule Networks: Relevance Path by Agreement., , , and . GlobalSIP, page 549-553. IEEE, (2018)COVID-CT-MD: COVID-19 Computed Tomography (CT) Scan Dataset Applicable in Machine Learning and Deep Learning., , , , , , , , , and . CoRR, (2020)COVID-FACT: A Fully-Automated Capsule Network-Based Framework for Identification of COVID-19 Cases from Chest CT Scans., , , , , , , , , and 1 other author(s). Frontiers Artif. Intell., (2021)COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans., , , , , , , and . CoRR, (2021)Robust Automated Framework for COVID-19 Disease Identification from a Multicenter Dataset of Chest CT Scans., , , , , , , , , and . CoRR, (2021)Improving the Accuracy of Beauty Product Recommendations by Assessing Face Illumination Quality., , , , and . CoRR, (2023)Spatio-Temporal Hybrid Fusion of CAE and SWin Transformers for Lung Cancer Malignancy Prediction., , , , , , and . ICASSP, page 1-5. IEEE, (2023)MDR-SURV: A Multi-Scale Deep Learning-Based Radiomics for Survival Prediction in Pulmonary Malignancies., , , and . ICASSP, page 2013-2017. IEEE, (2020)Capsule Networks for Brain Tumor Classification Based on MRI Images and Coarse Tumor Boundaries., , and . ICASSP, page 1368-1372. IEEE, (2019)From Hand-Crafted to Deep Learning-based Cancer Radiomics: Challenges and Opportunities., , , , and . CoRR, (2018)