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This website houses notes from my studies at the University of Liverpool. If you see any errors or issues, please do open an issue on this site's GitHub.

E-Commerce Introduction

COMP315 Lectures

What is Commerce Commerce is a transaction between two or more parties, in which something is exchanged and each party hopes to benefit. Party A party in commerce may be an individual or organisation. Things Things are goods (including money) or services (tangible or intangible). E-Commerce E-Commerce Commerce that is...

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Image Compression

ELEC319 Lectures

Lossless Compression Relies on probabilistic theory: Events that are less likely will contain more information. A measure of average information is entropy also known as Shannon’s Information Measure: \[H(x)=\sum_{i\in x}p(i)\log_2\left(\frac1{p(i)}\right)\] where: $x$ is a probabilistic experiment. $x_i$ are all the possible outcomes The base of the logarithm is the unit...

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Description Logic - Tableaux Method

COMP304 Lectures

Decision Method It is important to find a decision method for the consistency checking problem. The tableaux method allows us to solve this problem but only for acyclic knowledge bases. Using Concepts An atomic concept $A$ directly uses an atomic concept $B$ if there is a subsumption $A\sqsubseteq X$ or...

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Image Segmentation

ELEC319 Lectures

Segmentation is the separating of objects from the background. It divides images into regions. Edges & Regions Edge enhancement can divide images into regions: Each region is bounded by an edge. A threshold can detect edges in an edge enhanced image. Edge Linking Due to noise, edges may be unclear:...

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Edge Detection

ELEC319 Lectures

Always filter noise before using edge detection to improve the results. Derivative Filters Derivative (gradient) filters are used to enhance edges as they can highlight sudden changes in an image. The gradient operator is a vector function of a scalar field: \[\nabla f=\begin{pmatrix}\frac{\partial f}{\partial x}\\\frac{\partial f}{\partial y}\end{pmatrix}\] As we don’t...

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Description Logic - TBoxes & ABoxes

COMP304 Lectures

Subsumption In description logic we want to compare concepts to each other. Comparisons are called subsumptions. Subsumptions are of the form: $X\sqsubseteq Y$ The objects that satisfy $X$ are a subset of the objects that satisfy $Y$. $X\equiv Y$ The objects that satisfy $X$ are exactly the same as the...

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Building Maps

COMP329 Lectures

We have seen a couple of types of maps in prior lectures: Connecting Features Maps, Navigation & Path-finding this covers how to make these types of maps. The General Mapping Problem We can create a map from a run of: Controls (poses) Observations Given the sensor data and poses, we...

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Description Logic

COMP304 Lectures

Description logic is used to describe ontologies: An ontology defines objects by their relations to other objects. We have seen ontologies before in COMP111: Derived Assertions Algorithm Relations & Non-Unary Rule-Based Systems Language of ALC Attribute logic with complement (ALC) is a multi-agent modal logic (with different symbols). An ALC...

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Particle Filters

COMP329 Lectures

Markov localisation is very computationally and memory intensive as all the bins have to be updated. Particle filters use sampling techniques to reduce the number of possible positions, and number of calculations. We can describe the method like so: Given a space, generate randomly, a set of particles that generate...

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