The algorithm for the Transformer-DN model. by Liang Na (22226855)

PANet network design. by Mengqi Yuan (4852555)

“…<div><p>Millimeter-wave (mmWave) radar has become an important research direction in the field of object detection because of its characteristics of all-time, low cost, strong privacy and not affected by harsh weather conditions. …”

BiFPN network design. by Mengqi Yuan (4852555)

“…<div><p>Millimeter-wave (mmWave) radar has become an important research direction in the field of object detection because of its characteristics of all-time, low cost, strong privacy and not affected by harsh weather conditions. …”

Comparative data of different soil samples. by Gourab Saha (8987405)

Implementation of the low-discrepancy spherical trajectory in C++ from Selection and evaluation of spherical acquisition trajectories for industrial computed tomography by F. Bauer (10836998)

“…Inspired by pseudorandom sampling methods for Monte–Carlo-algorithms, we also suggest an entirely new trajectory design, the low-discrepancy spherical trajectory, which extends the concept of equiangular planar trajectories into three dimensions and can be used for benchmarking and comparison to other spherical trajectories. …”

Implementation of the low-discrepancy spherical trajectory and visualization in Matlab from Selection and evaluation of spherical acquisition trajectories for industrial computed t... by F. Bauer (10836998)

“…Inspired by pseudorandom sampling methods for Monte–Carlo-algorithms, we also suggest an entirely new trajectory design, the low-discrepancy spherical trajectory, which extends the concept of equiangular planar trajectories into three dimensions and can be used for benchmarking and comparison to other spherical trajectories. …”

Image 1_A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression.tif by Tingkai Hou (21014762)

“…</p>Methods<p>This paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. …”

Image 2_A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression.tif by Tingkai Hou (21014762)

“…</p>Methods<p>This paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. …”

Data Sheet 1_AutoRA: an innovative algorithm for automatic delineation of reference areas in support of smart soil sampling and digital soil twins.pdf by Hugo Rodrigues (5954366)

“…In this study, we introduce the autoRA algorithm, an innovative automated soil sampling design method that utilizes Gower’s Dissimilarity Index to delineate RAs automatically. …”

Big Data Model Building Using Dimension Reduction and Sample Selection by Lih-Yuan Deng (17081779)

“…Recently, several procedures have been proposed to select “optimal design points” as training subdata under pre-specified models, such as linear regression and logistic regression. …”

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”

3-D CNN decoder. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”

Learning of the transformer layer. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”

Original datasets for providing ROC-AUC curves. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”

ROC-AUC plot comparison of seven ML models. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”

Statistical performance of ML models. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”

Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”

Parameter settings. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”

Properties of datasets. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”

Feature embedding layer. by Xueliang Guo (4797057)

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”