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Physical Sciences and Mathematics Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Effective Plant Discrimination Based On The Combination Of Local Binary Pattern Operators And Multiclass Support Vector Machine Methods, Vi N T Le, Beniamin Apopei, Kamal Alameh
Effective Plant Discrimination Based On The Combination Of Local Binary Pattern Operators And Multiclass Support Vector Machine Methods, Vi N T Le, Beniamin Apopei, Kamal Alameh
Research outputs 2014 to 2021
Accurate crop and weed discrimination plays a critical role in addressing the challenges of weed management in agriculture. The use of herbicides is currently the most common approach to weed control. However, herbicide resistant plants have long been recognised as a major concern due to the excessive use of herbicides. Effective weed detection techniques can reduce the cost of weed management and improve crop quality and yield. A computationally efficient and robust plant classification algorithm is developed and applied to the classification of three crops: Brassica napus (canola), Zea mays (maize/corn), and radish. The developed algorithm is based on the …
Facial Re-Enactment, Speech Synthesis And The Rise Of The Deepfake, Nicholas Gardiner
Facial Re-Enactment, Speech Synthesis And The Rise Of The Deepfake, Nicholas Gardiner
Theses : Honours
Emergent technologies in the fields of audio speech synthesis and video facial manipulation have the potential to drastically impact our societal patterns of multimedia consumption. At a time when social media and internet culture is plagued by misinformation, propaganda and “fake news”, their latent misuse represents a possible looming threat to fragile systems of information sharing and social democratic discourse. It has thus become increasingly recognised in both academic and mainstream journalism that the ramifications of these tools must be examined to determine what they are and how their widespread availability can be managed.
This research project seeks to examine …
Anomaly Detection In Bacnet/Ip Managed Building Automation Systems, Matthew Peacock
Anomaly Detection In Bacnet/Ip Managed Building Automation Systems, Matthew Peacock
Theses: Doctorates and Masters
Building Automation Systems (BAS) are a collection of devices and software which manage the operation of building services. The BAS market is expected to be a $19.25 billion USD industry by 2023, as a core feature of both the Internet of Things and Smart City technologies. However, securing these systems from cyber security threats is an emerging research area. Since initial deployment, BAS have evolved from isolated standalone networks to heterogeneous, interconnected networks allowing external connectivity through the Internet. The most prominent BAS protocol is BACnet/IP, which is estimated to hold 54.6% of world market share. BACnet/IP security features are …
Rethinking Global-Regulation: World’S Law Meets Artificial Intelligence, Nachshon Sean Goltz, Addison Cameron-Huff, Giulia Dondoli
Rethinking Global-Regulation: World’S Law Meets Artificial Intelligence, Nachshon Sean Goltz, Addison Cameron-Huff, Giulia Dondoli
Research outputs 2014 to 2021
This article takes a critical look at Machine Translation of legal text, especially global legislation, through the discussion of Global-Regulation, a state of the art online search engine of the world’s legislation in English. Part 2 explains the rationale for an online platform such as Global-Regulation. Part 3 provides a brief account of the history of the development of machine translation, and it describes some of the limits of the use of statistical machine translation for translating legal texts. Part 4 describes Neural Machine Translation (NMT), which is a new generation of machine translation systems. Finally, Parts 5 and 6 …
Learning To Grasp In Unstructured Environments With Deep Convolutional Neural Networks Using A Baxter Research Robot, Shehan Caldera
Learning To Grasp In Unstructured Environments With Deep Convolutional Neural Networks Using A Baxter Research Robot, Shehan Caldera
Theses: Doctorates and Masters
Recent advancements in Deep Learning have accelerated the capabilities of robotic systems in terms of visual perception, object manipulation, automated navigation, and human-robot collaboration. The capability of a robotic system to manipulate objects in unstructured environments is becoming an increasingly necessary skill. Due to the dynamic nature of these environments, traditional methods, that require expert human knowledge, fail to adapt automatically. After reviewing the relevant literature a method was proposed to utilise deep transfer learning techniques to detect object grasps from coloured depth images. A grasp describes how a robotic end-effector can be arranged to securely grasp an object and …