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 10 of 10 for “"3D CNN"”.
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High-Resolution Additive Manufacturing Error Prediction and Compensation Through 3D CNN Leveraging Semantic Segmentation
… changes in geometry by training on segments of a 3D object rather than the whole object. Next, process parameters from fused-filament fabrication (FFF) processes were added to the ML models to add resilience process parameter variance. Lastly, the ML models were deployed in a federated environment …
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Visual Speech Recognition Using a 3D Convolutional Neural Network
… we present both a framework for building 3D feature cubes of lip data from videos and a 3D convolutional neural network (CNN) architecture for performing classification on a dataset of 100 spoken words, recorded in an uncontrolled envi- ronment. Our 3D-CNN architecture achieves a testing …
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Efficient Robotic Manipulation with Scene Knowledge
… network (HetGNN)-based coordinator and the 3D CNN-based actors. The system reasons about the relational knowledge between scene components and coordinates multiple robotic skills (e.g., grasping, pushing) to minimize the planning cost. As we anticipate an increase in the number of domestic …
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Online Spatiotemporal Action Detection and Prediction via Causal Representations
… performance to that of oine three dimensional (3D) convolutional neural networks (CNNs) on various tasks, including action recognition, temporal action segmentation and early prediction. To this end, we propose various action tube detection approaches from either single or multiple frames. We …
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Deep Learning-Based Brain Tumour Detection and Classification
… and final interpretation. Thus, the proposed CNN model serves as an efficient double-verification system that assists clinicians in identifying subtle tumour signatures, reduces oversight risk, and improves overall diagnostic throughput while maintaining human oversight at every stage. In this …
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Volumetric Medical Classification using Deep Learning: A comparative study on classifying Alzheimer's disease using Convolutional Neural Networks
… medical images benefits from the usage of 3D model architecture over traditional 2D architecture. In doing so, however, it is revealed that the 2D models do ultimately perform only slightly below the 3D model. Thus, the 2D approaches hold merit for potential usage, should a 2D planar …
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Advancing computational materials design and model development using data-driven approaches
… between and around sheets was unraveled using 3D Convolutional Neural Networks (3D-CNN). Specifically, through classification and regression models, water molecule ordering/disordering and atomic density profiles were accurately predicted, thereby elucidating nuanced interplays between sheet …
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The Influence of AR Head-Mounted Displays on Spatial Perception and Worker Response in Construction Training
… environment, deep learning models, including 2D CNN-LSTM sequence modeling and 3D CNN-LSTM architectures that are applied to predict temporal and cognitive state changes from 4D EEG input (frequency, amplitude, time, channels), extending the framework from measurement to prediction. Together, …
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Advancing Electrical Stimulation: Full-Head MRI Segmentation for Abnormal Brain Anatomy with tDCS
… three 2D convolutional neural networks (CNNs) along the sagittal, axial, and coronal planes, followed by a 3D CNN to produce a unified segmentation. Unlike conventional methods, it does not rely on a tissue probability map (TPM), making it robust to anatomical abnormalities seen in …
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Developing Deep-Learning Methods for Diagnosis and Prognosis of Pediatric Progressive Diseases Using Modern Imaging Techniques
… Automated medical image analysis tools based on 3D/2D deep learning algorithms can help improve the quality and consistency of image diagnosis and interpretation for cognitive disorders in infants. We propose to automate neuroimaging analysis with artificial intelligence algorithms. This novel …