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.
Results
Showing 1 to 20 of 33 for “"large-scale dataset"”.
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SmellNet: A Large-scale Dataset for Real-world Smell Recognition
… these broad impacts, there are virtually no large-scale benchmarks, and therefore little progress, for training and evaluating AI systems’ ability to smell in the real world. In this paper, we use portable gas and chemical sensors to create SmellNet, the first large-scale database that …
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Face distance : unpacking the role of ethnic ties in venture capital investment
… between investors and entrepreneurs in a large scale dataset of realized and potential investments. Results suggest that previous work has vastly underestimated the relationship between ethnic ties and investment. Moreover, this relationship is more nuanced than previously documented, …
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Localized Visual Aberration Detection and Suppression Dataset for UAV Perception Systems
… (fog, glare, dust). This thesis presents a large-scale dataset with a variety of scenes in both a simulated and real world indoor environments containing both visual and dynamical sensor data measured in the presence of varying levels of localized smoke sources. This dataset aims to …
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A fine-grained geospatial representation and framework for large-scale indoor environments
… augmenting, and distributing the resulting large-scale dataset. Lastly, it showcases an array of applications, and proposes others, which utilize the representation and dataset to provide rich location-based services within indoor environments.
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Pre-integrated dynamics factors and a dynamical agile visual-inertial dataset for UAV perception
… graph visual-inertial odometry (VIO), and a large-scale dataset with a great variety of visual, inertial, and dynamical sensor data from a quadrotor platform. The pre-integrated dynamics factors were tested on a challenging subset of the dataset and showed an improvement in robustness of a …
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Two approaches to robust hand pose estimation : generative modeling and semantic relations
… Spurred by the lack of occlusion in hand image datasets, we present the MIT Partially Occluded Hands Dataset, a large-scale dataset of single RGB images, half of which feature natural hand-object interactions, and evaluate several baselines on this dataset.
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Fine-grained memory access over I/O interconnect for efficient remote sparse data access
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms
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Inferring Shape and Material from Sound
… to rely on supervised learning, which requires a large-scale dataset containing sounds of various objects, with clean labels on their appearances, shape and material. However, it is difficult and expensive to capture such a dataset. Another approach is to tackle the problem in an …
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Deidentification of Face Videos in Naturalistic Driving Scenarios
… Extensive experimentation is conducted using a large-scale dataset from ORNL, enabling the quantification of errors associated with head movements, mouth movements, eye movements, and other human factors cues. Additionally, qualitative analysis using metrics such as PERCLOS (Percentage of Eye …
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Scalable Data Paradigms for Steering General-Purpose Language Models
… of the SuperNaturalInstructions benchmark—a large-scale dataset with over 1,600 NLP tasks—I demonstrate that unifying NLP tasks via natural language instructions enables model generalization at the task level. Second, I propose Self-Instruct, a novel framework where LMs generate their own …
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Discovering and Personalizing Artistic Styles with Generative Models
… effort, we curate and release STYLEBREEDER, a large-scale dataset comprising 6.8 million images and 1.8 million text prompts from 95,000 users, along with clustering annotations and stylistic embeddings. We also introduce the Style Atlas platform, providing public access to 100 curated style …
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Manifold aligned density estimation
… data we are facing today is growing in both the scale and the dimensionality dramatically. It thus raises new challenges for some traditional machine learning tasks. This thesis is mainly concerned with manifold aligned density estimation problems. In particular, the work presented in this thesis …
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Photorealistic sensor simulation for perception-driven robotics using virtual reality
… facility. Second, we present The Blackbird Dataset, a large-scale dataset for UAV perception in aggressive flight containing over 10 hours of flight data across 171 flights at velocities up to 13.8ms⁻¹ in 5 environments with some dynamic elements. Third, we introduce a virtual reality …
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Enabling Accurate and High-Throughput Kinetics Predictions via Message Passing Neural Networks
… cost severely limits their utility for large-scale applications. High-quality experimental data is often even more rare, and such approaches are less amenable to exploring the vastness of chemical space due to monetary cost, time, and safety considerations. Modern machine learning (ML) …
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A Depth-Guided Annotation Tool for B-Line Quantification in Lung Ultrasound
… at Harvard-affiliated institutions, to support large-scale dataset curation, gold-standard adjudication, and AI model development. This tool addresses a critical gap in structured LUS annotation workflows by enabling reproducible, sector-based quantification of B-lines and pleural features. Its …
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Digital Humans: Improving Appearance Rendering, Advancing Motion Retargeting
… Second, the scarcity of comprehensive 4D human datasets is tackled by presenting a large-scale dataset of high-resolution textured meshes, enriched with extensive ground truth annotations. This dataset bridges a critical gap in the literature, offering the first large scale high-quality virtual …
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Credit card fraud detection using incremental feature learning
… used sub-models. There are a limited number of datasets for credit card fraud detection available due to the data sensitivity issue. So, we have evaluated our approach using two of the existing datasets: A mid-scale dataset consisting of two days of European cardholders’ transactions in …
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Classifying and Displaying Brain-waves through Self-supervised Learning
… of medical training. Hence, constructing labeled datasets for supervised learning from EEG signals is expensive and time-consuming. Moreover, the existing datasets use incompatible EEG setups (e.g. different numbers of channels, sampling rates, types of sensors, etc.) that make them hard to fuse …
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Interactive visualization of the collaborative research network
… their entities. In this research, we focus on a large scale dataset known as the Digital Bibliography and Library Project or DBLP, which contains information on all publications that have been published in computer and information science related journals and conference proceedings. We model the …
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Automatic Semantic Segmentation Of Kidney Tumors In Computed Tomography Images
… in cross-sectional images, but unlike for large well-defined regions like major organs and bones, the performance on small, poorly-circumscribed structures in unpredictable locations, such as lesions, remains relatively poor. This dissertation presents a series of contributions throughout …
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