Pre-processing of raw images for pose estimation using physical model-trained convolutional neural network model. by Aniket Ravan (3174171)

Experimental setup and trajectory estimation methodology. by Nouman Javed (16624785)

ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... by G. Christopher Marais (21492084)

Fig 12 - by Nisha Yadav (366131)

Table_1_Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model.docx by Chenglin Wang (430151)

“…The R-LBP algorithm, an extension of the LBP algorithm, enhances the texture features of citrus fruits at distinct ripeness stages by calculating the coefficient of variation in grayscale values of pixels within a certain range in different directions around the target pixel. …”

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

“…From the results obtained across these three real scenarios explored in this thesis, it is possible to see that the proposed methodology achieves better performances than sampling in a structured regular grid (used as a conventional rule for sampling) in terms of both error in image reconstruction and global economic value, when considering the economic revenue of processing the ore and dumping the waste. <br><br>It is important to emphasize that no previous work have addressed the optimal sensing problem covered in this thesis for characterization of geological fields in the context of \emph{<i>MPS</i>}. …”

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

“…Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). …”