Deep Learning For Image Analysis

21 Nov 2018 in Teaching

I was a teaching assistant for the segmentation practical sessions for the course Deep Learning For Image Analysis given in the ATHENS Programme by Etienne Decencière, Santiago Velasco-Forero and Thomas Walter. I animated a practical session on tissue segmentation, the notebook and presentation can be found in github and the data can be found here.

About

I am currently a post doctoral researcher looking for real world applications to which apply my skills in computer vision.

My main research interest concerns the development of statistical, machine learning and deep learning models for real world applications in computer vision. I am particularly interested in modelling complex, low sampled and high dimensional data. I have mostly applied my research to the bioimaging field and in particular to large 2D images (>60GB when uncompressed), 3D imaging and video data. Applying my research to these goal oriented projects and tackling inherent difficulties in the data has led to me to build a keen interest in transfer learning and learning from imperfect and noisy data, which includes weakly supervised learning and self-supervised learning.

I am very interest in collaborating on bioimage related topics and also in applying my research to new fields and to cross different input modalities such as sound, satellite imaging and gene expression data.

Please do not hesitate to reach out.

Deep Learning For Image Analysis

Peter Jack Naylor

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