Search Results for author:
Found 5 papers, 3 papers with code
The (de)biasing effect of GAN-based augmentation methods on skin lesion images
In addition, we examined classification models trained on both real and synthetic data with counterfactual bias explanations.
Joint prediction of truecasing and punctuation for conversational speech in low-resource scenarios
Further, we show that by training the model in the written text domain and then transfer learning to conversations, we can achieve reasonable performance with less data.
Waste detection in Pomerania: non-profit project for detecting waste in environment
Our team conducted comprehensive research on Artificial Intelligence usage in waste detection and classification to fight the world's waste pollution problem.
Ranked #1 on
Object Detection
on Extended TACO-1
Towards explainable classifiers using the counterfactual approach -- global explanations for discovering bias in data
The paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data.
Style transfer-based image synthesis as an efficient regularization technique in deep learning
In a proposed approach, the newly created images are described with pseudo-labels, and then used as a training dataset.
