ENL of homogeneous regions within the filtering results of each algorithm. by Haiyan Zhang (176919)

The denoising results of the urban region. by Haiyan Zhang (176919)

The denoising results of the mountain region. by Haiyan Zhang (176919)

The denoising results of the farmland region. by Haiyan Zhang (176919)

The denoising results of the coastal region. by Haiyan Zhang (176919)

Four images need to be denoised, with yellow and blue marked areas indicating homogeneous regions. by Haiyan Zhang (176919)

HMM to infer selection. by Adam G. Fine (21763286)

Simulated Atomic Force Microscopy (SimAFM) of SecYEG. by Creighton M. Lisowski (22756444)

Practical implementation of an End-to-end methodology for SPC of 3-D part geometry: A case study by Yulin An (833223)

Structures of naked SFV virion, SFV in complex with LA3, and SFV in complex with LA5. by Decheng Yang (349886)

Albedo Retrievals from MODIS Over the Sea of Okhotsk (Validation Data, 2002–2014) by Yingzhen Zhou (19723405)

“…<p dir="ltr">This dataset contains satellite-based albedo retrievals and surface classifications from MODIS sensors over the Sea of Okhotsk, collected during multiple voyages of the Soya Icebreaker from 2002 to 2014. …”

Forest cover and canopy health mapping in Australian subalpine landscape: supervised machine learning models for Sentinel-2 and Landsat images by Weerach Charerntantanakul (21532661)

“…We tested random-forest (RF), support vector machine (SVM), and multiple linear regression (MLR) to find the algorithm that provides the best accuracy. …”

Data Sheet 1_Automated classification of MESSENGER plasma observations via unsupervised transfer learning.pdf by Vicki Toy-Edens (21758102)

“…We applied an unsupervised clustering algorithm, initially trained on data from the Magnetospheric Multiscale (MMS) mission at Earth, to MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) observationsat Mercury to identify three distinct plasma regions: magnetosphere, magnetosheath, and solar wind. …”

Modified laser scanned point cloud dataset of a modern wind turbine support tower by Lijithan Kathirkamanathan (19813146)

“…</p><h3>Scanning methodology</h3><p dir="ltr">The painted outer surface of the WTST was laser scanned from ground level from multiple positions around the WTST using a Leica ScanStation P40 with the maximum available scanning resolution. …”

Landscape17 by Vlad Carare (22092515)

“…This dataset features global potential energy surface representations generated using the energy landscape framework and includes regions crucial for accurately reproducing both thermodynamic and kinetic properties. …”

Global hourly seamless AOD through measurement-adjusted machine learning fusion of multi-satellite and reanalysis data by Yu Ding (54012)

“…To overcome these limitations, this study proposes an AOD fusion framework that integrates measurement adjustment theory with a machine learning algorithm to combine multiple satellite AOD products with the MERRA−2 reanalysis dataset. …”

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

“…</li><li>Site Identification: For that time step, the model identifies and maps candidate projects with the lowest Levelized Cost of Energy (LCOE) that are required to meet the capacity target within a given Queensland region.</li><li>Capacity Allocation: If sufficient suitable sites are unavailable within the target region due to land-use constraints, the remaining required capacity is automatically allocated to the next nearest region with available resources.…”