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 6 of 6 for “"Image-based deep learning"”.
-
Image-based deep learning approaches for plant phenotyping
… to challenges in available phenotyping methods. Deep learning could be used to build automatic tools for identifying, localizing and quantifying plant features based on agricultural images. This dissertation describes the development and evaluation of state-of-the-art deep learning approaches for …
-
Improving breast cancer risk assessment with image-based deep learning models
… reduce the rich information contained in the image down to a single number. In this thesis, I present deep learning models that predict breast cancer risk directly from full images, specifically breast MRIs and mammograms. Our image-based deep learning models out-perform existing breast cancer …
-
Advancing single cell microbiology and bacteriophage-bacteria interactions using microfluidics and image-based deep learning
… effective therapies. Conventional culture-based assays are often slow, labour-intensive, and limited in their ability to capture the heterogeneous responses of individual bacteria to antibiotics or bacteriophages. This thesis addresses these challenges by developing integrated, label-free, …
-
Deep learning in sequential data analysis
Deep learning has achieved great success in recent years in computer vision and its related areas. For core computer vision tasks such as image classification, image semantic segmentation, image super-resolution, and object detection from images, deep learning based methods outperform various …
-
Deep Learning for Short-Term Spatiotemporal Prediction of Shared Dockless E-Scooter Demand: Grid-Based Representation, Temporal Input Design, and Day-Type-Aware Model Benchmarking
… prediction, literature still lacks a coherent image-based deep learning framework. This is important because e-scooter demand is naturally distributed over urban space, and image-based models can learn spatial dependencies directly from demand maps. Moreover, prior studies often under-document …
-
Reconstruction of cross-modal visual features from acoustic pressure time series in combustion systems
… is detecting combustion instability using flame images where deep learning frameworks have demonstrated high performance. The proposed frameworks are shown to be quite trustworthy such that the domain experts can have sufficient confidence to use these models in real systems to prevent unwanted …