Maria Ferlin
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View article: Targeted data augmentation for improving model robustness
Targeted data augmentation for improving model robustness Open
This paper proposes a new and effective bias mitigation method called targeted data augmentation (TDA). Since removing biases is often tedious and challenging and may not always lead to effective bias mitigation, we propose an alternative …
View article: Quantifying inconsistencies in the Hamburg Sign Language Notation System
Quantifying inconsistencies in the Hamburg Sign Language Notation System Open
The advent of machine learning (ML) has significantly advanced the recognition and translation of sign languages, bridging communication gaps for hearing-impaired communities. At the heart of these technologies is data labeling, crucial fo…
View article: Targeted data augmentation for improving modelrobustness against systematic bias
Targeted data augmentation for improving modelrobustness against systematic bias Open
The paper proposes a new and effective bias mitigation method called Targeted Data Augmentation (TDA). Since removingbiases is a tedious, always difficult and, on the other hand, not necessarily an effective approach the authors propose to…
View article: Targeted Data Augmentation for bias mitigation
Targeted Data Augmentation for bias mitigation Open
The development of fair and ethical AI systems requires careful consideration of bias mitigation, an area often overlooked or ignored. In this study, we introduce a novel and efficient approach for addressing biases called Targeted Data Au…
View article: Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges Open
This paper provides the first review to date which gathers, describes, and assesses, to the best of our knowledge, all available publications on automating cerebral microbleed (CMB) detection. It provides insights into the current state of…
View article: Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach Open
Breast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligenc…
View article: Deep learning-based waste detection in natural and urban environments
Deep learning-based waste detection in natural and urban environments Open
Waste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards…
View article: A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System Open
Machine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It…
View article: Waste detection in Pomerania: non-profit project for detecting waste in environment
Waste detection in Pomerania: non-profit project for detecting waste in environment Open
Waste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, either for economic or ecological reasons, and the industry demands high efficiency. Our team conducted com…