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Skip to Search Results- 4Convolutional Neural Networks
- 1Computer Vision
- 1Differentiable Programming
- 1Dynamic Programming
- 1Earth Observation
- 1End-to-end Learning
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An Interactive 3D Visualization Tool to Analyze the Functionality of Convolutional Neural Networks
DownloadFall 2022
Convolutional Neural Networks have outperformed traditional image processing approaches for many image classification tasks. However, despite achieving high classification accuracy on multiple datasets, these machine learning approaches are not transparent and act more like a black box. For this...
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Fall 2015
Determining the viewpoint (pose) of rigid objects in images is a classic vision problem with applications to robotic grasping, autonomous navigation, augmented reality, semantic SLAM and scene understanding in general. While most existing work is characterized by phrases such as "coarse pose...
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Fall 2024
Remote sensing is an effective tool to monitor and assess the dynamics across the Earth’s surface. Despite significant technological advancements, there remains a constant demand for high-resolution remote sensing data in spatial, spectral, and temporal contexts. Such high-resolution data is...
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Extending Differentiable Programming to include Non-differentiable Modules using Differentiable Bypass for Combining Convolutional Neural Networks and Dynamic Programming into an End-to-end Trainable Framework
DownloadSpring 2019
Differentiable Programming is the paradigm where different functions or modules are combined into a unified pipeline with the purpose of applying end-to-end learning or optimization. A natural impediment is the non-differentiability characteristic of many modules. This thesis proposes a new way...