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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Pothole Detection Under Diverse Conditions Using Object Detection Models, Ibrahim Hassan Syed, Dympna O'Sullivan, Susan Mckeever
Pothole Detection Under Diverse Conditions Using Object Detection Models, Ibrahim Hassan Syed, Dympna O'Sullivan, Susan Mckeever
Conference papers
One of the most important tasks in road maintenance is the detection of potholes. This process is usually done through manual visual inspection, where certified engineers assess recorded images of pavements acquired using cameras or professional road assessment vehicles. Machine learning techniques are now being applied to this problem, with models trained to automatically identify road conditions. However, approaching this real-world problem with machine learning techniques presents the classic problem of how to produce generalisable models. Images and videos may be captured in different illumination conditions, with different camera types, camera angles, and resolutions. In this paper, we present our …
Interrupting The Propaganda Supply Chain, Kyle Hamilton, Bojan Bozic, Luc Longo
Interrupting The Propaganda Supply Chain, Kyle Hamilton, Bojan Bozic, Luc Longo
Conference papers
In this early-stage research, a multidisciplinary approach is presented for the detection of propaganda in the media, and for modeling the spread of propaganda and disinformation using semantic web and graph theory. An ontology will be designed which has the theoretical underpinnings from multiple disciplines including the social sciences and epidemiology. An additional objective of this work is to automate triple extraction from unstructured text which surpasses the state-of-the-art performance.
K-Nearest Neighbour Classifiers - A Tutorial, Padraig Cunningham, Sarah Jane Delany
K-Nearest Neighbour Classifiers - A Tutorial, Padraig Cunningham, Sarah Jane Delany
Conference papers
Perhaps the most straightforward classifier in the arsenal or Machine Learning techniques is the Nearest Neighbour Classifier – classification is achieved by identifying the nearest neighbours to a query example and using those neighbours to determine the class of the query. This approach to classification is of particular importance because issues of poor run-time performance is not such a problem these days with the computational power that is available. This paper presents an overview of techniques for Nearest Neighbour classification focusing on; mechanisms for assessing similarity (distance), computational issues in identifying nearest neighbours and mechanisms for reducing the dimension of …