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Found 6 papers, 3 papers with code
Prompt-driven Latent Domain Generalization for Medical Image Classification
To address these challenges, we propose a novel DG framework for medical image classification without relying on domain labels, called Prompt-driven Latent Domain Generalization (PLDG).
EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition
Concretely, EPVT leverages a set of domain prompts, each of which plays as a domain expert, to capture domain-specific knowledge; and a shared prompt for general knowledge over the entire dataset.
Transmission-Guided Bayesian Generative Model for Smoke Segmentation
To effectively model the two types of uncertainty, we introduce a Bayesian generative model to simultaneously estimate the posterior distribution of model parameters and its predictions.
Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decision
We introduce a human-in-the-loop framework in the model training process such that users can observe and correct the model's decision logic when confounding behaviors happen.
An overlapping-free leaf segmentation method for plant point clouds
The proposed method can also facilitate the automatic traits estimation of each single leaf (such as the leaf area, length, and width), which has potential to become a highly effective tool for plant research and agricultural engineering.
An Integrated Image Filter for Enhancing Change Detection Results
In this paper, we present an integrated filter which comprises a weighted local guided image filter and a weighted spatiotemporal tree filter.
