Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 10 of 10 for “"Superpixels"”.
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Superpixels for Hyperspectral Image Analysis
… methods that efficiently and robustly exploits superpixels for hyperspectral data. We study and quantify the efficacy of state-of-the-art superpixel generation algorithms for a variety of hyperspectral images. In this work, superpixel level analysis is proposed for two different hyperspectral …
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Superpixel Segmentation of Outdoor Webcams to Infer Scene Structure
… a lot of memory. This thesis explores the use of superpixels to address these issues. Superpixels, an approach to image segmentation, over-segment a scene but attempt to ensure that each segment lies on only one scene element. Applying superpixels to webcams reduces the e∩¼Çect of noise on …
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Multi-scale local explanation approach for image analysis using model-agnostic explainable artificial intelligence (XAI)
… explanation highlighting the most important superpixels affecting the CNN’s decision. This thesis aims to explore and develop a multi-scale scheme of LIME to explain decisions made by CNN models through heatmaps of coarse to finer scales. More precisely, when LIME highlights large superpixels …
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Superpixel Segmentation Systems: Design and Analysis
… order of 105 – 107 pixels to a few hundreds of superpixels. Thereby, the computation time is greatly reduced for further post-processing steps such as region merging for image segmentation, object tracking, detection, depth estimation, object recognition, image denoising, object-based …
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Deep learning for digitized histology image analysis
… Deep learning-based nuclei detection by superpixels was performed as an extension of our research. Results from this research indicate an improved performance of CIN assessment over state-of-the-art methods for nuclei segmentation, epithelium segmentation, and CIN classification, as well …
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Robust graph transduction
… so that the saliency values of all the superpixels are decided from simple superpixels to more difficult ones. The difficulty of a superpixel is judged by its informativity, individuality, inhomogeneity, and connectivity. As a result, our saliency detector generates manifest saliency …
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A Study on Deep Learning: Training, Models and Applications
… a pre-defined cost function. Moreover, SLIC superpixels and low level saliency features are applied to smooth and refine the saliency maps. Experimental results have shown that the proposed methods can generate high-quality salience maps. The last method is also for image saliency detection. …
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Development of computer-based algorithms for unsupervised assessment of radiotherapy contouring
… and region-based) and graph-cut applied on superpixels were explored. k-nearest neighbour (k-NN) classification of tumour from normal tissues based on texture features was also investigated. RESULTS: 63 cases were used for development and training. Segmentation and classification performance …
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Development of image analysis techniques to enable low-cost tropical rain forest monitoring
… to break up imagery over management units into superpixels, and through a combination of spectral and textural patterns in the imagery, train an automatic classifier to detect the species of interest from UAV imagery. I then show the power of this approach to map prevalence of key tree species …
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Tumour Localisation in Histopathology Images
Immunohistochemical (IHC) assessment in cancer research is important for understanding the distribution and localisation of biomarkers at the cellular level. However currently IHC analyses are predominantly performed manually, increasing workloads and introducing inter- and intra-observer …