To incur in the ks project, the following readings:
- On the in vivo recognition of kidney stones using machine learning [Paper] 🌟
- Assessing deep learning methods for the identification of kidney stones in endoscopic images [Paper]
- Classification of Stones According to Michel Daudon: A Narrative Review [Paper] 🌟
- Evaluation and understanding of automated urinary stone recognition methods [Paper] 🌟
- Boosting kidney stone identification in endoscopic images using two-step transfer learning [Paper] [Repo]
- Improved kidney stone recognition through attention and multi-view feature fusion strategies [Paper]
- On the generalization capabilities of FSL methods through domain adaptation: a case study in endoscopic kidney stone image classification [Paper]
- Improving automatic endoscopic stone recognition using a multi-view fusion approach enhanced with two-step transfer learning [Paper]
- Evaluating the plausibility of synthetic images for improving automated endoscopic stone recognition [Paper]
- A metric learning approach for endoscopic kidney stone identification [Paper]
🌟 Mandatory paper
I will soon add the respective repositories
Last updated by Francisco: 11 Sept '24