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 19 of 19 for “"Scene classification"”.
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Context and configuration based scene classification
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
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Natural scene classification, annotation and retrieval. Developing different approaches for semantic scene modelling based on Bag of Visual Words.
… thesis investigates three main problems: natural scene classification, annotation and retrieval. Given an image, the task is to design a system that can determine to which class that image belongs to (classification), what semantic concepts it contain (annotation) and what images are most similar …
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Joint spatial and layer attention for convolutional networks
… freedom camera pose regression and (ii) indoor scene classification. Empirically, we show that combining the “what” and “where” aspects of attention improves network performance on both tasks. We evaluate our method on standard benchmarks for camera localization (Cambridge, 7-Scenes, and …
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The effect of scene content on image quality
… perform well on individual ‘average looking’ scenes and test targets, but provide lower correlation with subjective assessments when working with a variety of scenes with different than ‘average signal’ characteristics. This study considers the issues of scene dependency on image quality. This …
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A Fuzzy Logic-Based System for Soccer Video Scenes Classification
… in the processing of video footage only. Classification problems in recorded videos are often very complex and uncertain due to the dynamic nature of the video sequence and light conditions, background, camera angle, occlusions, indistinguishable scene features, etc. Video scene …
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Hierarchical density estimation for image classification
… have been widely used in patch-based image classification problems. Despite the satisfactory results reported, both methods suffer from a number of disadvantages. For instance, a histogram may be easy to learn but has a large quantization error; on the contrary, Gaussian mixture model based …
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Connecting Deep Learning Models to the Human Brain
… in tasks such as object recognition, scene classification, and language processing, achieving near-human accuracy in some cases. This raises intriguing questions about how closely the computations and geometric structure of these models mirror that of the human brain. Our method starts …
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Machines' perception of space
… simulate behaviors including space composition classification, space scene classification, 3D reconstruction of space, space rating and algebraic operations of space. These aspects cover topics ranging from pure geometrical understandings to semantic reasoning and emotional feelings of space. …
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Learning-based Methods for Occluder-aided Non-Line-of-Sight Imaging
Imaging scenes that are not in our direct line-of-sight, referred to as non-line-of-sight (NLOS) imaging, has recently gained considerable attention from the computational imaging community. With a diverse set of potential applications in several domains, NLOS imaging is an emerging topic with many …
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Organising and structuring a visual diary using visual interest point detectors
… in the object detection and recognition and scene classification fields, there is little work in the area of setting detection. Furthermore, few authors have examined the issues involved in analysing extremely large image collections (like a Visual Diary) gathered over a long period of time. …
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Detecting semantic concepts in digital photographs: low-level features vs. non-homogeneous data fusion
… if ease of access and use is to be ensured. Classification of images into broad categories such as indoor/outdoor, building/non-building, urban/landscape, people/no-people, etc., allows us to obtain the semantic labels without the full knowledge of all objects in the scene. Inferring the …
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Deep image representation learning for knowledge discovery from earth observation data archives
… while a particular attention is devoted to image scene classification and content-based image retrieval (CBIR) problems due to their importance for large-scale knowledge discovery. In detail, we propose five DL-based IRL methods throughout the thesis. First, a multi-label classification approach …
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VISUAL AND SEMANTIC KNOWLEDGE TRANSFER FOR NOVEL TASKS
… have surpassed human performance on ImageNet classification, which consists of millions of labeled images. However, one challenge in conventional supervised learning systems is their generalization ability. Once a model is trained on a specific dataset, it can only perform the task on those …
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Sparse modeling of high-dimensional data for learning and vision
… inpainting, compressive sensing, pattern classification, and blind source separation. In this dissertation, we learn the sparse representations of high-dimensional signals for various learning and vision tasks, including image classification, single image super-resolution, compressive …
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Robust Deep Learning Methodologies for Weakly Supervised Remote Sensing Image Classification
… supervised learning (WSL) in RS with a focus on classification tasks such as land-cover mapping and scene classification. WSL strategies are commonly subdivided into three different categories: i) inaccurate supervision, which deals with label noise; ii) inexact supervision, which deals with …
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Adaptive Processing of Laser Scanning Data and Texturing of the Segmentation Outcome
… site modelling). However, no interpretation and scene classification is performed during data acquisition. Consequently, the collected data must be processed to extract the required information. To date, a variety of techniques have been developed for the processing of laser scanning data, but …
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Novel color and local image descriptors for content-based image search
Content-based image classification, search and retrieval is a rapidly-expanding research area. With the advent of inexpensive digital cameras, cheap data storage, fast computing speeds and ever-increasing data transfer rates, millions of images are stored and shared over the Internet every day. …
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Generation and analysis of segmentation trees for natural images
… we successfully use them as priors in image classification and semantic image segmentation. We also investigate the importance of different visual cues to describe image regions for solving the region correspondence problem. We design and develop psychophysical experiments to learn the …