title: Perceptual improvements for Super-Resolution of Satellite Imagery

authors: Bull, Dainel

subjects: computer science

abstract: Super-resolution of satellite imagery poses unique challenges. We propose a hybrid method comprising two existing deep network super-resolution approaches, namely a feedforward network called DeepSUM, and ESRGAN, a GAN-based approach, to super-resolve multiple low-resolution images by a factor of four to obtain a single high-resolution image. We also introduce a novel loss function, called variation loss, to better define edges and textures to create a sharper, perceptually better output. Using our hybrid, we inherit some of the advantages of both deep learning approaches, resulting in super-resolved images that better show boundaries, textures, and details.

text: Perceptual improvements for Super-Resolution of Satellite Imagery Super-resolution of satellite imagery poses unique challenges. We propose a hybrid method comprising two existing deep network super-resolution approaches, namely a feedforward network called DeepSUM, and ESRGAN, a GAN-based approach, to super-resolve multiple low-resolution images by a factor of four to obtain a single high-resolution image. We also introduce a novel loss function, called variation loss, to better define edges and textures to create a sharper, perceptually better output. Using our hybrid, we inherit some of the advantages of both deep learning approaches, resulting in super-resolved images that better show boundaries, textures, and details.

year: 2021

title: Effects of a small-bladed macroalgal canopy on benthic boundary layer dynamics: implications for nutrient transport

authors: Kregting, Louise T.

subjects: macroalgae

abstract: Field and laboratory velocity profiles were used to quantify boundary layer dynamics within communities of a small (<0.2 m tall), dense canopy-forming seaweed Adamsiella chauvinii (Rhodophyta) in a soft-sediment habitat and to examine the role of hydrodynamics in modulating nutrient supply. At the ‘canopy scale’ there was a mixing layer at the fluid−canopy interface where turbulent kinetic energy was greatest, potentially enhancing nutrient uptake in this region. In the lower half of the canopy, a drag-dominated area of very low water velocity (<0.01 m s−1) occurred. Spectral analysis revealed a reduction in energy within the canopy of around 1 Hz. The hydrodynamic parameters obtained from flume measurements were in good agreement with those recorded in the field. To understand the implications of the hydrodynamic environment on nutrient uptake, a flushing ratio was developed that compares the time for macroalgae to remove all nutrients from the canopy volume relative to the timescale for flushing. Results suggest that when nutrient demand is low, the canopy is well flushed and not mass-transfer limited. However when nutrient demand is high, the canopy can deplete nutrients more quickly than they can be replenished by ambient flows and are potentially mass-transfer limited.

text: Effects of a small-bladed macroalgal canopy on benthic boundary layer dynamics: implications for nutrient transport Field and laboratory velocity profiles were used to quantify boundary layer dynamics within communities of a small (<0.2 m tall), dense canopy-forming seaweed Adamsiella chauvinii (Rhodophyta) in a soft-sediment habitat and to examine the role of hydrodynamics in modulating nutrient supply. At the ‘canopy scale’ there was a mixing layer at the fluid−canopy interface where turbulent kinetic energy was greatest, potentially enhancing nutrient uptake in this region. In the lower half of the canopy, a drag-dominated area of very low water velocity (<0.01 m s−1) occurred. Spectral analysis revealed a reduction in energy within the canopy of around 1 Hz. The hydrodynamic parameters obtained from flume measurements were in good agreement with those recorded in the field. To understand the implications of the hydrodynamic environment on nutrient uptake, a flushing ratio was developed that compares the time for macroalgae to remove all nutrients from the canopy volume relative to the timescale for flushing. Results suggest that when nutrient demand is low, the canopy is well flushed and not mass-transfer limited. However when nutrient demand is high, the canopy can deplete nutrients more quickly than they can be replenished by ambient flows and are potentially mass-transfer limited.

year: 2011

title: Māori loanwords: a corpus of New Zealand English tweets

authors: Trye, David

abstract: Māori loanwords are widely used in New Zealand English for various social functions by New Zealanders within and outside of the Māori community. Motivated by the lack of linguistic resources for studying how Māori loanwords are used in social media, we present a new corpus of New Zealand English tweets. We collected tweets containing selected Māori words that are likely to be known by New Zealanders who do not speak Māori. Since over 30% of these words turned out to be irrelevant (e.g., mana is a popular gaming term, Moana is a character from a Disney movie), we manually annotated a sample of our tweets into relevant and irrelevant categories. This data was used to train machine learning models to automatically filter out irrelevant tweets.

text: Māori loanwords: a corpus of New Zealand English tweets Māori loanwords are widely used in New Zealand English for various social functions by New Zealanders within and outside of the Māori community. Motivated by the lack of linguistic resources for studying how Māori loanwords are used in social media, we present a new corpus of New Zealand English tweets. We collected tweets containing selected Māori words that are likely to be known by New Zealanders who do not speak Māori. Since over 30% of these words turned out to be irrelevant (e.g., mana is a popular gaming term, Moana is a character from a Disney movie), we manually annotated a sample of our tweets into relevant and irrelevant categories. This data was used to train machine learning models to automatically filter out irrelevant tweets.

year: 2019