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Consortium of Swiss Academic Libraries

Classification of thoracolumbar fractures and dislocations

Aebi, Max

In: European Spine Journal, 2010, vol. 19, p. 2-7

Consortium of Swiss Academic Libraries

Twin Boosting: improved feature selection and prediction

Bühlmann, Peter ; Hothorn, Torsten

In: Statistics and Computing, 2010, vol. 20, no. 2, p. 119-138

Consortium of Swiss Academic Libraries

Horses for courses

Sartorius, N.

In: Epidemiology and Psychiatric Sciences, 2012, vol. 21, no. 3, p. 265-266

Haute école de santé Genève

La classification du rythme cardiaque foetal par catégories permet-elle de prédire le statut acido-basique artériel ombilical néonatal ? : travail de Bachelor

Géry, Charlène ; Potter, Katherine ; Kaiser, Barbara (Dir.)

Mémoire de bachelor : Haute école de santé Genève, 2014.

Contexte : Lors de son introduction dans les années 1960, la cardiotocographie promettait de réduire de moitié la mortalité intrapartum et la parésie cérébrale. Aujourd’hui, le constat est que si elle réduit le taux de convulsions néonatales, la surveillance du rythme cardiaque foetal n’améliore pas le taux de parésies cérébrales, et est même associée à une augmentation des...

Università della Svizzera italiana

Advances in deep learning for vision, with applications to industrial inspection : classification, segmentation and morphological extensions

Masci, Jonathan ; Schmidhuber, Jürgen (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2014 ; 2014INFO001.

Learning features for object detection and recognition with deep learning has received increasing attention in the past several years and recently attained widespread popularity. In this PhD thesis we investigate its applications to the automatic surface inspection system of our industrial partner ArcelorMittal, for classification and segmentation problems. Currently employed algorithms, in...

Université de Fribourg

Empirical comparison of local structural similarity indices for collaborative-filtering-based recommender systems

Zhang, Qian-Ming ; Shang, Ming-Sheng ; Zeng, Wei ; Chen, Yong ; Lü, Linyuan

In: Physics Procedia, 2010, vol. 3, no. 5, p. 1887-1896

Collaborative filtering is one of the most successful recommendation techniques, which can effectively predict the possible future likes of users based on their past preferences. The key problem of this method is how to define the similarity between users. A standard approach is using the correlation between the ratings that two users give to a set of objects, such as Cosine index and Pearson...