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CS

Carola Schönlieb

05/10/18

@ Y Combinator

Denoising is integrated into the image reconstruction process, addressing both the lack of data and the noise present in measurements.

Video

YC

Mathematical Approaches to Image Processing with Carola Schönlieb

@ Y Combinator

Mathematical Approaches to Image Processing with Carola Schönlieb

05/10/18

Related Takeaways

CS

Carola Schönlieb

05/10/18

@ Y Combinator

Successful image denoising methods focus on preserving edges, which are crucial for maintaining the integrity of the image's features.

CS

Carola Schönlieb

05/10/18

@ Y Combinator

The integration of handcrafted models with neural networks presents exciting opportunities for mathematicians to explore and improve image denoising techniques.

CS

Carola Schönlieb

05/10/18

@ Y Combinator

The challenge in CT imaging is that the data collected is often insufficient for high-resolution images, leading to noise in the measurements.

CS

Carola Schönlieb

05/10/18

@ Y Combinator

The goal in training a neural network for denoising images is to minimize the least squares error between the denoised and clean images across the training set.

CS

Carola Schönlieb

05/10/18

@ Y Combinator

While handcrafted models for image denoising are still relevant, deep neural networks are increasingly outperforming them in various scenarios.

CS

Carola Schönlieb

05/10/18

@ Y Combinator

Total variation regularization is a widely used technique in image denoising that helps preserve sharp discontinuities in images.

FL

Fei-Fei Li

09/21/24

@ a16z

Nerf, or Neural Radiance Fields, represents a breakthrough in backing out 3D structure from 2D observations, merging reconstruction and generation in computer vision.

CS

Carola Schönlieb

05/10/18

@ Y Combinator

In my postdoc, I shifted towards inverse imaging problems, where the observed data is not a direct image but a transform, such as in CT scans.

CS

Carola Schönlieb

05/10/18

@ Y Combinator

In collaborations with hospitals, we focus on developing algorithms that maximize the quality of high-resolution images from limited data, particularly in medical imaging.