Abstract: This paper proposes an application-oriented condition monitoring method for power semiconductor switches, which constructs a robust health indicator with high robustness, low sampling rate, ...
The sequence of amino acids within a protein dictates its structure and function. Protein engineering campaigns seek to discover protein sequences with desired functions. Data-driven models of the ...
Abstract: In this manuscript, we propose to use a variational autoencoder-based framework for parameterizing a conditional linear minimum mean squared error estimator ...
Same as traditional autoencoders, VAE architecture has two parts: an encoder and a decoder. Traditional AE models map inputs into a latent-space vector and reconstruct the output from this vector. VAE ...
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 ...
Image enhancement is considered to be one of the complex tasks in image processing. When the images are captured under dim light, the quality of the images degrades due to low visibility degenerating ...
Most existing image dehazing methods based learning are less able to perform well to real hazy images. An important reason is that they are trained on synthetic hazy images whose distribution is ...
Although practically attractive with high prediction and classification power, complicated learning methods often lack interpretability and reproducibility, limiting their scientific usage. A useful ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results