Celldetective is an open-source software integrating segmentation, tracking, and event detection to perform high-throughput end-to-end study of dynamic cell interactions, without requiring coding ...
Abstract: The effectiveness of spectral-spatial feature learning is crucial for the hyperspectral image (HSI) classification task. Diffusion models, as a new class of groundbreaking generative models, ...
Aims This study aims to investigate whether denoising diffusion probabilistic models (DDPMs) could generate realistic retinal images, and if they could be used to improve the performance of a deep ...
Abstract: Cross-domain few-shot learning (CDFSL) has demonstrated remarkable new class recognition capabilities in hyperspectral image classification (HSIC) tasks. However, existing domain adaptation ...
Latent Diffusion Autoencoders (LDAE) is a novel unsupervised framework for representation learning in 3D medical imaging. The method compresses 3D MRI scans using an AutoencoderKL, then applies a ...
Neurodegenerative diseases such as Alzheimer's disease (AD) or frontotemporal lobar degeneration (FTLD) involve specific loss of brain volume, detectable in vivo using T1-weighted MRI scans.
The success of deep learning is often attributed to its ability to harness the hierarchical and compositional structure of data. However, formalizing and testing this notion remained a challenge. This ...
Counterfactual explanations (CEs) aim to enhance the interpretability of machine learning models by illustrating how alterations in input features would affect the resulting predictions. Common CE ...
Synthetic Aperture Radar (SAR) plays a crucial role in all-weather and all-day Earth observation owing to its distinctive imaging mechanism. However, interpreting SAR images is not as intuitive as ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results