Comparison of output from the online tool implementing the algorithm and human raters. by Charu Manivannan (9726301)

Algorithm to assemble composite index maps from multi-criteria analysis of geographic data. by Md. Anwar Uddin (14341697)

Supplementary file 1_3D colored point cloud classification of a deep-sea cold-water coral and sponge habitat using geometric features and machine learning algorithms.docx by Salem Morsy (10840104)

Spatial variation from 2014 to 2017. by Lei Liang (326409)

China’s annual forest age dataset at a 30-m spatial resolution from 1986 to 2022 by Rong Shang (17306089)

Comparison of maps obtained by the three algorithms. by Hiroki Mizuochi (12360087)

Performance metrics for mapping tools derived from mouse kidney data. by Huamei Li (8815955)

Evaluating and mapping spatial drought in northeast Thailand: utilizing analytic hierarchy process and random forest algorithms by Zahid Naeem Qaisrani (21567311)

“…The AHP model achieved an overall accuracy (OA) of 85.19%, aligning closely with the RF model, which had an OA of 88.89%. The RF algorithm effectively mapped spatial drought events with high accuracy, as confirmed by comparisons with rainfall data. …”

Accuracy metrics of mapping tools on spatial transcriptomics (ST) data from multiple tissues. by Huamei Li (8815955)

Figure 6 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

Figure 5 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

Figure 2 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

Table 1 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

Table 2 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

Figure 4 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

Figure 3 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

Figure 1 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

“…The cell detection algorithm generates a cell probability map. A postprocessing algorithm was developed to find the cell nucleus center, (<i>x</i>, <i>y</i>) location, from the probability map (Supplementary Materials and Methods). …”

Error maps of selected spatial models. by Cristian Valeriu Patriche (16872029)

“…<div><p>Various research topics from the field of soil science or agriculture require digital maps of soil properties as input data. …”

Supplementary Table 10 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies by Yeman Brhane Hagos (17885432)

Spatial comparison of community detection algorithms. by Hamish Gibbs (9548952)