Spatial characterization and cell-type-specific genes in mouse brain tissue. by Huamei Li (8815955)

Evaluation of spatial transcriptomics (ST) tools across various metrics and conditions. by Huamei Li (8815955)

BootCellNet2 gives clustering that comply more with CITE-seq results. by Yutaro Kumagai (481168)

LandScan Global, 30 Arc-second Annual Global Gridded Population Datasets from 2000 to 2022 by Viswadeep Lebakula (16069243)

“…Using an innovative approach that combines geospatial science, remote sensing technology, and machine learning algorithms, LandScan Global is a global population distribution data, at 30 arc seconds (roughly 1km at equator), representing an ambient (24 hour average) population. …”

Overall framework design. by Matthew Yit Hang Yeow (20721206)

“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”

Gamma distribution of reuse. by Matthew Yit Hang Yeow (20721206)

“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”

Top 5 correlated features based on reuse. by Matthew Yit Hang Yeow (20721206)

“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”

Features with the top importance score. by Matthew Yit Hang Yeow (20721206)

“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”

Heatmap of pre-post interview changes in system insights, health equity thinking, & healthy equity action. by Travis R. Moore (19532635)

S1 Graphical abstract - by José M. Rivera-Arbeláez (12418512)

“…The software uses a shape-detection algorithm to single out and track the movement of pillars’ tips for the most common shapes of EHT platforms. …”

Quantitative results on WEDU dataset. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Counting results on DRPD dataset. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Quantitative results on RFRB dataset. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Main module structure. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Counting results on MTDC-UAV dataset. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Quantitative results on DRPD dataset. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Architecture of MAR-YOLOv9. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Quantitative results on MTDC-UAV dataset. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Counting results on WEDU dataset. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”

Example images from four plant datasets. by Dunlu Lu (19964225)

“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”