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 13 of 13 for “"Dataset Creation"”.
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Engaging people in ethical AI development: Design, dataset creation, and decision-making
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01
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A fast selective grasping algorithm with deep learning and autonomous dataset creation on point cloud
… To expedite the training process, an autonomous dataset generation method is proposed. This method eliminates the need for manual annotation by autonomously generating data, and training is conducted within a simulation environment, such as Isaac Sim or any other simulation that allows object …
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Hierarchical, informed and robust machine learning for surgical tool management
… accomplished included the development of a new dataset, creation of state of the art techniques to cope with volume, variety and vision problems, and designing or adapting algorithms to address specific surgical tool recognition issues. The system was trained to cope with a wide variety of …
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AKF: A modern synthesis framework for building datasets in digital forensics
… validation, and research. However, real-world datasets often contain sensitive information that may be difficult to remove, making them challenging to distribute publicly. As a result, researchers and educators can encounter gaps in available datasets, typically leading to the manual …
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InjectBench: An Indirect Prompt Injection Benchmarking Framework
… and subsequently use this newly created dataset to do preliminary testing on defenses against indirect prompt injections. Experiment results suggest that while more capable models are susceptible to attacks, they are better equipped at utilizing defense strategies. To summarize, our work …
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From Data, to Models, and Back: Making Machine Learning Predictably Reliable
… within this pipeline: model deployment (Part I), dataset creation (Part II), data collection (Part III), and algorithm selection (Part IV). For each of these design choices, we use targeted experiments to uncover the corresponding principles that actually underlie the behavior of ML systems. We …
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Karma Chameleons: Data Collection Techniques and Account Characterization for Bot Detection on Reddit
… the collection of bot or human account datasets with a clearly established ground truth that can be used to train machine learning models. Without these datasets, developing accurate models to distinguish between bot and human accounts becomes difficult. In contrast to Twitter/X, bot …
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Fast Supervised Annotation and Active Learning with Uncertainty for Cloud Mask Dataset Generation
… due to difficulty generating robust, labeled datasets for complex learners. Variation in data and diverse tasks make it difficult to both generally crowd source to build such datasets, and to offload this responsibility to the small number of expert annotators that exist. Currently, no general …
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Acquiring and Harnessing Verb Knowledge for Multilingual Natural Language Processing
… informs the development of a two-phase semantic dataset creation methodology, which combines semantic clustering with fine-grained semantic similarity judgments collected through spatial arrangements of lexical stimuli. The method is tested on English and then applied to a typologically diverse …
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What is the Multi-Party Trick? Language and Interactions in Multi-Party Conversations during the Era of LLMs
… of LLMs to generate large-scale synthetic MPC datasets under explicit structural constraints. Our results show that LLMs can produce structurally diverse and controllable conversations, especially by using a multi-step generation strategy. However, human evaluation highlights persistent …
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Provident Vehicle Detection at Night in Urban Scenarios
… of user studies and their evaluation, - a novel dataset to address the task of detecting oncoming vehicles at night in urban scenarios based on light reflections, with a particular focus on the challenge of achieving high-quality annotations in the light of limited human effort, and - a proposal …
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Advanced Deep Learning Methods for the Automatic Analysis of Radar Sounder Data
… reducing the manual effort required for dataset creation. Second, we address the challenge of learning from weak supervision by designing a novel deep neural architecture incorporating a convolutional recurrent bottleneck and vertical nonlocal operations. This method explicitly models the …
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Automating microscopic image analysis post-photolithography with machine learning
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms