Publication

Learning-based approaches for feature fusion in multi-modal indoor localization

2020
Student Projects

Abstract

Due to their aptitude to capture complex dependencies, neural networks are a promising candidate for indoor localization. Omnipresent phenomena such as multi-path signal propagation, shadowing and device noise introduce non-linear effects in the data, and make conventional geometry-based methods fail even in simple environments. This semester project explores few analytical outlier rejection algorithms and new fusion methods based on neural networks and compares them with an analytical model.

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2020
Student Projects

Abstract

Official source

Related concepts (31)

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

Types of artificial neural networks

There are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.

Phenomenon-based learning

Phenomenon-based learning (PhBL, PhenoBL or PBL) is a multidisciplinary, constructivist form of learning or pedagogy where students study a topic or concept in a holistic approach instead of in a subject-based approach. PhBL includes both topical learning (also known as topic-based learning or instruction), where the phenomenon studied is a specific topic, event, or fact, and thematic learning (also known as theme-based learning or instruction), where the phenomenon studied is a concept or idea.

Related publications (32)

Learning-based approaches for feature fusion in multi-modal indoor localization

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