Quality check in Skin Cancer AI

Skin is the largest organ of human body and skin cancer is the most common cancer in the world. Skin cancer is deadly at late stage when cancer spreads to internal organs. However, if being detected early, skin cancer can be cured with high survival rate.

Round table on Ethical AI in Smart Cities

iToBoS project recently took part in a round table discussion on the ethical use of artificial intelligence (AI) in city infrastructure and planning, led by the Economics Program at the Center for Strategic and International Studies (CSIS).

Image Colour Correction

Image colour correction is the task of altering the colours in an image to match the wanted colours, usually the colours humans perceived at the scene acquisition. One popular way of doing that is by using a Colour Checker.

Convolutional Neural Networks (CNN) for image processing

Convolutional neural networks are a type of neural networks often used to perform machine learning techniques on images.

The changing landscape of AI regulation

Until a few years ago, regulations and standards existed around the handling and use of certain types of data, including the General Data Protection Regulation (GDPR)[1] in Europe, HIPAA[2] and PCI-DSS[3] in the United States, the Canadian Consumer Privacy Protection Act (CPPA)[4] and many more.

[FR] iToBoS presented at Actu Toulouse

iToBoS project was presented in Actu Toulouse, a digital newspaper that publishes articles on the daily life of the inhabitants of Toulouse and its region, portraits, ideas for outings, tips and practical information. The article is written in French.

An Introduction to Generative Adversarial Networks (GAN)

Generative Adversarial Networks are unsupervised neural networks that are able to analyse information from a dataset and produce similar new samples.

Economic burden of skin cancers in Europe

As observed by Dr Eline Noels of the Erasmus University of Rotterdam, the knowledge of the economic burden of skin cancers is “essential to enable health policy decision-makers to make well-informed decisions on potential interventions and to be able to evaluate the future effect of these decisions”.

EPLL: image denoising using a Gaussian Mixture Model learned on a large set of patches

For image denoising, there is an important line of work that uses the self-similarity principle that natural images obey: an image contains many image patches similar between each other. To remove noise, one can look for similar patches in an image and average them.

Uncertainty Estimation in Deep Neural Networksfor Dermoscopic Image Classification

Machine learning and specifically deep learning, have dramatically improved the state-of-the-art in many areas of research, including computer vision, speech recognition, and natural language processing.