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 14 of 14 for “"Interactive machine learning"”.
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Guided Interactive Machine Learning
… the Crayons image classifier system and active learning. Currently Crayons provides no guidance to the user in what pixels should be labeled or when the task is complete. This work focuses on two main areas: 1) active learning for user guidance, and 2) accuracy estimation as a measure of …
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Insight : interactive machine learning for complex graphics selection
… selections. This thesis explores the use of interactive machine learning techniques to improve direct selection interfaces. To investigate this approach, I created Insight, an interactive machine learning selection tool for making a relevant class of complex selections: visually similar …
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Obstacle Avoidance and Path Traversal Using Interactive Machine Learning
… obstacle avoidance. This definition system uses interactive machine learning to ensure that the obstacle avoidance is both easy for a human operator to use and can perform well in different environments. Initial, real world tests show that system is effective at automatic obstacle avoidance.
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Visual Analytics and Interactive Machine Learning for Human Brain Data
… of two parts: multi-modal data visualization and interactive machine learning. For multi-modal data visualization, a major challenge is how to integrate structural, functional and connectivity data to form a comprehensive visual context. We develop a new integrated visualization solution for brain …
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Interactive Machine Learning for Refinement and Analysis of Segmented CT/MRI Images
This dissertation concerns the development of an interactive machine learning method for refinement and analysis of segmented computed tomography (CT) images. This method uses higher-level domain-dependent knowledge to improve initial image segmentation results. A knowledge-based refinement and …
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News Matter : embedding human intuition in machine intelligence through interactive data visualizations
… they come in as an unstructured text that for machines is hard to generalize. While numerous tools exist that use Natural Language Processing to identify features of news articles, few use NLP to help readers navigate the universe of news stories. This thesis proposes a novel interaction …
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Mitigating Compute Congestion for Low Latency Datacenter RPCs
… in recent datacenter workloads, such as interactive machine learning inference, high-frequency algorithm trading, cloud gaming, and interactive AR/VR applications impose stringent latency requirements. These applications heavily rely on low-latency RPCs as an essential building block, …
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Making computer vision Methods accessible for cell classification
… higher level understanding. Recent advances in machine learning such as deep learning based architectures have greatly expanded their potential. However, biologists often lack the training or means to use new software or algorithms, leading to slower or less complete results. This thesis focuses …
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Open Coding for Machine Learning
… to reducing this bias include incorporating interactive machine learning techniques, modifying the input features of the algorithm, or improving the pre-processing of the dataset [35]. However, even if the prediction model is fair and the raw dataset is fair, unfair labels still present the …
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User Interfaces for an Open Source Indicators Forecasting System
… back to raw feeds. Finally, we present an interactive machine learning approach for analysts to steer the construction of machine learning mod-els. This provides fine-grained control into tuning tradeoffs underlying EMBERS. Together, these three interfaces support a range of functionality …
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Integrating Systems, Processes, and Human Judgment: Three Essays on Value Creation with Supply Chain Analytics
<p>Big-data, analytics, automation, and machine learning are changing the role of managers in supply chain and operations functions. Extant research indicates that effective value creation by analytics is achieved through careful attention to three components: technology, people, and processes. As …
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Human-Machine Alignment for Context Recognition in the Wild
… is, what she is doing and with whom – allows the machine to represent the world in user’s terms. The context must be inferred from a stream of sensor readings generated by smart wearables such as smartphones and smartwatches, and the labels are acquired from the user directly. To perform robust …
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SAMPLS: A prompt engineering approach using Segment-Anything-Model for PLant Science research
… Anything Model (SAM) to evaluate its zero-shot learning capability and whether prompt engineering can reduce the effort and time consumed in dataset annotation, facilitating a semi-automated training process. Our proposed method improved the detection rate of cells and reduced the error rate as …
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AI-Supported Interactive Segmentation of 3D Volumes
… These features serve as the foundation to learning the proposed voxelwise classifiers and to discriminate between segmented and unsegmented voxels. On the one hand, they perform fully automated clustering of volumes for which a representative random sample is extracted first. On the other …