17 citations · 21 across the 3 of their papers we have counts for
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Impact of Labeling Inaccuracy and Image Noise on Tooth Segmentation in Panoramic Radiographs using Federated, Centralized and Local Learning
Johan Andreas Balle Rubak, Khuram Naveed, Sanyam Jain +3
Objectives: Federated learning (FL) may mitigate privacy constraints, heterogeneous data quality, and inconsistent labeling in dental diagnostic AI. We compared FL with centralized…
PanoDiff-SR: Synthesizing Dental Panoramic Radiographs using Diffusion and Super-resolution
Sanyam Jain, Bruna Neves de Freitas, Andreas Basse-OConnor +2
Interest in generating realistic synthetic medical images has grown in recent years. Such datasets can mitigate the scarcity of public data for artificial intelligence research and…
NAADA: A Noise-Aware Attention Denoising Autoencoder for Dental Panoramic Radiographs
Khuram Naveed, Bruna Neves de Freitas, Ruben Pauwels
Convolutional denoising autoencoders (DAEs) are powerful tools for image restoration. However, they inherit a key limitation of convolutional neural networks (CNNs): they tend to r…