Now showing items 1-5 of 5
Enhancing performance of conventional image codecs using CNN based image sub-sampling and super resolution
The goal of image compression is to reduce the number of bits required to represent an image with a minimum loss of visual quality. However, conventional image compression algorithms, such as JPEG, produce unpleasant ...
Deep learning techniques applied to the remote sensing of soil moisture and sea ice type
This thesis presents deep learning techniques applied to the modeling of geophysical quantities with remote sensing data to estimate soil moisture and classify sea ice type. The objective of the thesis is to determine if ...
Improving cross-dataset generalization in image classification with contrastive representation learning
Regular monitoring of marine wildlife is essential for rapid detection of changes in the marine ecosystem allowing for adaptive strategies. However, the manual analysis of large volumes of underwater images taken by cameras ...
Signal parameter estimation of damped sinusoidal waveforms using deep learning
Sinusoids and damped signals are a fundamental part of different engineering fields. Analysis of these signals to give an accurate estimation of certain parameters such as frequency, damping factor, and phase angle is ...
Data collection using deep reinforcement learning for serious games
Mild Cognitive Impairment (MCI) often occurs prior to the more serious condition of dementia and early detection of MCI is an important but challenging task because of its indistinct symptoms. Work has been done developing ...