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Metric learning for kernel ridge regression: assessment of molecular similarity

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Dynamic media content categorisation method

Sabine Süsstrunk, Mahmut Sami Arpa, Gabriel Albert Autes

The present invention concerns a method of classifying a media item into a user profile suitability class in a classification system comprising a set of pre-trained artificial neural networks. The method comprising: receiving (101) a media file; extracting ...

2020

Regression Networks for Meta-Learning Few-Shot Classification

Matthias Grossglauser, Arnout Jan J Devos

We propose regression networks for the problem of few-shot classification, where a classifier must generalize to new classes not seen in the training set, given only a small number of examples of each class. In high dimensional embedding spaces the directi ...

2020

Language Independent Query by Example Spoken Term Detection

Dhananjay Ram

Language independent query-by-example spoken term detection (QbE-STD) is the problem of retrieving audio documents from an archive, which contain a spoken query provided by a user. This is usually casted as a hypothesis testing and pattern matching problem ...

EPFL2019

Unpaired Cross-Spectral Pedestrian Detection Via Adversarial Feature Learning

Seungryong Kim

Even though there exist significant advances in recent studies, existing methods for pedestrian detection still have shown limited performances under challenging illumination conditions especially at nighttime. To address this, cross-spectral pedestrian de ...

IEEE2019

A novel biomechanical approach for animal behaviour recognition using accelerometers

Kamiar Aminian, Pritish Chakravarty

Data from animal-borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have b ...

2019

Incorporating long-range physics in atomic-scale machine learning

Michele Ceriotti, Andrea Grisafi

The most successful and popular machine learning models of atomic-scale properties derive their transferability from a locality ansatz. The properties of a large molecule or a bulk material are written as a sum over contributions that depend on the configu ...

2019

Machine learning for cross-gazetteer matching of natural features

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Defining and identifying duplicate records in a dataset is a challenging task which grows more complex when the modeled entities themselves are hard to delineate. In the geospatial domain, it may not be clear where a mountain, stream, or valley ends and be ...

2019

Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise

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In presence of sparse noise we propose kernel regression for predicting output vectors which are smooth over a given graph. Sparse noise models the training outputs being corrupted either with missing samples or large perturbations. The presence of sparse ...

IEEE2019

Light Field Synthesis Using Inexpensive Surveillance Camera Systems

We present a light field synthesis technique that achieves accurate reconstruction given a low-cost, wide-baseline camera rig. Our system integrates optical flow with methods for rectification, disparity estimation, and feature extraction, which we then fe ...

2019

Deep Feature Factorization for Concept Discovery

Sabine Süsstrunk, Radhakrishna Achanta, Edo Collins

We propose Deep Feature Factorization (DFF), a method capable of localizing similar semantic concepts within an image or a set of images. We use DFF to gain insight into a deep convolutional neural network's learned features, where we detect hierarchical c ...

SpringerLink2018

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