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 20 of 22 for “"image understanding"”.
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Language-Centric Medical Image Understanding
This thesis advances medical image understanding by leveraging the multifaceted roles of language: as supervision, prior knowledge, and a medium for communication. We introduce three main contributions: (1) a weakly supervised framework that uses language in clinical reports to guide fine-grained …
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Image understanding and feature extraction for applications in industry and mapping
… information of a scene from a number of images. Existing photogrammetric systems are semi-automatic requiring manual editing and control, and have very limited domains of application so that image understanding capabilities are left to the user. Among the most important steps in a fully …
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Prime component decomposition of images and its applications in an image understanding system
… crucial requirements in the development of an image understanding system (IUS). In this thesis, a model for the low-level processing stage based on a new scheme of prime component decomposition is proposed. This model is then used to develop a knowledge-based image understanding system that is …
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Multi-Level Learning Approaches for Medical Image Understanding and Computer-aided Detection and Diagnosis
… the area of diagnostic radiology and medical image analysis. This thesis presents two multi-level learning-based approaches for medical image understanding with applications of CAD/CADx. The so-called "multi-level learning strategy" relies on that supervised and unsupervised statistical …
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Content-based Image Understanding with Applications to Affective Computing and Person Recognition in Natural Settings
Understanding the visual content of images is one of the most important topics in computer vision. Many researchers have tried to teach the machine to see and perceive like human. In this dissertation, we develop several new approaches for image understanding with applications to affective …
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Content-based image analysis with applications to the multifunction printer imaging pipeline and image databases
<p>Image understanding is one of the most important topics for various applications. Most of image understanding studies focus on content-based approach while some others also rely on meta data of images. Image understanding includes several sub-topics such as classification, segmentation, …
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Fast object detection
… goal of computer vision is to understand images. We describe methods to understand images at two levels. One is at the level of description of images which we produce using sentences. These sentences talk about the things that are present in the image and about where they are and what they …
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ScatterNet Hybrid Frameworks for Deep Learning
Image understanding is the task of interpreting images by effectively solving the individual tasks of object recognition and semantic image segmentation. An image understanding system must have the capacity to distinguish between similar looking image regions while being invariant in its response …
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Addressing Occlusion in Panoptic Segmentation
… deep learning. Despite the gains in performance, image understanding algorithms are still not completely robust to partial occlusion. In this work, we propose a novel object classification method based on compositional modeling and explore its effect in the context of the newly introduced panoptic …
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Automated interpretation of digital images of hydrographic charts.
… is presented. Low level processing of digital images of hydrographic charts provides image line feature segments which serve as input to a semi-automated feature extraction system, (SAFE). This system is able to perform a great deal of the building of chart features from the image segments …
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Anomaly detection and prediction of human actions in a video surveillance environment
… these suggestions by combining the fields of image understanding and artificial intelligence, specifically Bayesian Networks, to develop a prototype video surveillance system that can learn common environmental behaviour patterns, thus being able to detect and predict anomalous activity in the …
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Childhood obesity and its prevention in primary school-aged children: a focus on South Asian communities in the UK
… children by exploring its association with body image. Understanding the psychosocial consequences of obesity in target communities will enable future interventions to be appropriately designed. The findings of this thesis highlight the importance of understanding the cultural context with …
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Uses of Complex Wavelets in Deep Convolutional Neural Networks
Image understanding has long been a goal for computer vision. It has proved to be an exceptionally difficult task due to the large amounts of variability that are inherent to objects in a scene. Recent advances in supervised learning methods, particularly convolutional neural networks (CNNs), have …
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Novel Texture-based Probabilistic Object Recognition and Tracking Techniques for Food Intake Analysis and Traffic Monitoring
<p>More complex image understanding algorithms are increasingly practical in a host of emerging applications. Object tracking has value in surveillance and data farming; and object recognition has applications in surveillance, data management, and industrial automation. In this work we introduce an …
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Constraint-Based Interpolation
Image reconstruction is the process of converting a sampled image into a continuous one prior to transformation and resampling. This reconstruction can be more accurate if two things are known: the process by which the sampled image was obtained and the general characteristics of the original …
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Pipelines for Computational Social Science Experiments and Model Building
… in robotics, genetics, automated systems, and image understanding, but have largely been devoid of human behavior. We use these pipelines to understand intra-group cooperation and its effect on fostering CI. We devise and execute an iterative abductive analysis process that is driven by the …
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Circular Probabilistic Based Color Processing: Applications in Digital Pathology Image Analysis
… which fosters the research of digital pathology image understanding and automatic cancer diagnosis to address challenges in pathology. Color plays a vital role in digital pathology image analysis due to the use of chemical staining in pathology examination. However, unclear color mixing due to …
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Multimodal Foundation Models through the Lens of Security: Robust Deepfake Detection and Adversarial Resilience
… process multiple types of data, such as text, images, video as input and output, enabling seamless interaction across different modalities. Examples include Text-to-Image (T2I) generation models like DALL-E and Stable Diffusion, which create highly realistic images from simple text prompts. …
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