Search Results - "Debattista, Kurt"

An Empirical Evaluation of the Effectiveness of Attack Graphs and Fault Trees in Cyber-Attack Perception by Lallie, Harjinder Singh, Debattista, Kurt, Bal, Jay

“…Perceiving and understanding cyber-attacks can be a difficult task. This problem is widely recognized and welldocumented, and more effective techniques are…”
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Deep HDR Hallucination for Inverse Tone Mapping by Marnerides, Demetris, Bashford-Rogers, Thomas, Debattista, Kurt

“…Inverse Tone Mapping (ITM) methods attempt to reconstruct High Dynamic Range (HDR) information from Low Dynamic Range (LDR) image content. The dynamic range of…”
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Subjective and Objective Evaluation of Local Dimming Algorithms for HDR Images by Duan, Lvyin, Debattista, Kurt, Lei, Zhichun, Chalmers, Alan

“…In order to enhance viewing experiences, a number of backlight local dimming (BLD) algorithms have been developed to improve the image contrast ratio and…”
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High Dynamic Range Imaging and Low Dynamic Range Expansion for Generating HDR Content by Banterle, Francesco, Debattista, Kurt, Artusi, Alessandro, Pattanaik, Sumanta, Myszkowski, Karol, Ledda, Patrick, Chalmers, Alan

“…In the last few years, researchers in the field of High Dynamic Range (HDR) Imaging have focused on providing tools for expanding Low Dynamic Range (LDR)…”
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A Significance Cache for Accelerating Global Illumination by Bashford-Rogers, Thomas, Debattista, Kurt, Chalmers, Alan

“…Rendering using physically based methods requires substantial computational resources. Most methods that are physically based use straightforward techniques…”
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Learning Preferential Perceptual Exposure for HDR Displays by Bashford-Rogers, Thomas, Melo, Miguel, Marnerides, Demetris, Bessa, Maximino, Debattista, Kurt, Chalmers, Alan

“…High dynamic range (HDR) displays are capable of displaying a wider dynamic range of values than conventional displays. As HDR content becomes more ubiquitous,…”
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Virtual Category Learning: A Semi-Supervised Learning Method for Dense Prediction With Extremely Limited Labels by Chen, Changrui, Han, Jungong, Debattista, Kurt

“…Due to the costliness of labelled data in real-world applications, semi-supervised learning, underpinned by pseudo labelling, is an appealing solution…”
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A review of attack graph and attack tree visual syntax in cyber security by Lallie, Harjinder Singh, Debattista, Kurt, Bal, Jay

“…Perceiving and understanding cyber-attacks can be a difficult task, and more effective techniques are needed to aid cyber-attack perception. Attack modelling…”
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Region-Object Relation-Aware Dense Captioning via Transformer by Shao, Zhuang, Han, Jungong, Marnerides, Demetris, Debattista, Kurt

“…Dense captioning provides detailed captions of complex visual scenes. While a number of successes have been achieved in recent years, there are still two broad…”
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Textual Context-Aware Dense Captioning with Diverse Words by Shao, Zhuang, Han, Jungong, Debattista, Kurt, Pang, Yanwei

“…Dense captioning generates more detailed spoken descriptions for complex visual scenes. Despite several promising leads, existing methods still have two broad…”
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HDR video past, present and future: A perspective by Chalmers, Alan, Debattista, Kurt

“…High dynamic range (HDR) video has emerged from research labs around the world and entered the realm of consumer electronics. The dynamic range that a human…”
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Semi-supervised Unpaired Medical Image Segmentation Through Task-affinity Consistency by Chen, Jingkun, Zhang, Jianguo, Debattista, Kurt, Han, Jungong

“…Deep learning-based semi-supervised learning (SSL) algorithms are promising in reducing the cost of manual annotation of clinicians by using unlabelled data,…”
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A review on chemometric techniques with infrared, Raman and laser-induced breakdown spectroscopy for sorting plastic waste in the recycling industry by Neo, Edward Ren Kai, Yeo, Zhiquan, Low, Jonathan Sze Choong, Goodship, Vannessa, Debattista, Kurt

“…•A comprehensive review of IR, Raman and LIBS for plastic sorting is performed.•Scope of plastic studied should be expanded to represent heterogenous plastic…”
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DCMSTRD: End-to-end Dense Captioning via Multi-Scale Transformer Decoding by Shao, Zhuang, Han, Jungong, Debattista, Kurt, Pang, Yanwei

“…Dense captioning creates diverse Region of Interests (RoIs) descriptions for complex visual scenes. While promising results have been obtained, several issues…”
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Accelerating Stereo Image Simulation for Automotive Applications Using Neural Stereo Super Resolution by Haghighi, Hamed, Dianati, Mehrdad, Donzella, Valentina, Debattista, Kurt

“…Camera image simulation is integral to the virtual validation of autonomous vehicles and robots that use visual perception to understand their environment. It…”
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Generating Synthetic Training Images to Detect Split Defects in Stamped Components by Singh, Aru Ranjan, Bashford-Rogers, Thomas, Hazra, Sumit, Debattista, Kurt

“…Detecting rare and costly defects, such as necks and splits in sheet metal stamping, remains challenging for deep learning models due to low failure rates…”
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Perception-based high quality distributed virtual reality by Naylor, William, Debattista, Kurt, Chalmers, Alan

“…Virtual reality has great potential to enable remote collaborative work from anywhere in the world. Developing virtual reality into a platform suitable for…”
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Using virtual environments to facilitate refugee integration in third countries by Kirya, Mark, Debattista, Kurt, Chalmers, Alan

“…Virtual experiences (VEs) have significant potential to enrich emotional interactions, to encourage socialisation and improve communication. In education, VEs…”
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Deep Controllable Backlight Dimming for HDR Displays by Duan, Lvyin, Marnerides, Demetris, Chalmers, Alan, Lei, Zhichun, Debattista, Kurt

“…High dynamic range (HDR) displays with dual-panels are one type of displays that can provide HDR content. These are composed of a white backlight panel and a…”
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Dynamic contrastive learning guided by class confidence and confusion degree for medical image segmentation by Chen, Jingkun, Chen, Changrui, Huang, Wenjian, Zhang, Jianguo, Debattista, Kurt, Han, Jungong

“…This work proposes an intra-Class-confidence and inter-Class-confusion guided Dynamic Contrastive (CCDC) learning framework for medical image segmentation. A…”
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