YOLOv8 model architecture diagram. by Xiaozhou Feng (2918222)

“…This study pioneers the detection of pine wilt disease-infected trees in the China’s Qinba Mountain region, where the complex terrain and uneven forest distribution thinder feature extraction of diseased trees. To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”

FLMP-YOLOv8 architecture diagram. by Xiaozhou Feng (2918222)

“…This study pioneers the detection of pine wilt disease-infected trees in the China’s Qinba Mountain region, where the complex terrain and uneven forest distribution thinder feature extraction of diseased trees. To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”

High-entropy sulfide data for clustering comparison by Alexander Eggeman (11230284)

“…<p dir="ltr">Unsupervised machine learning algorithms are applied to two different sets of scanning transmission electron microscope data. …”

(a). Comparison of Translation Accuracy. by Na Wang (193263)

Data Sheet 1_Evaluating methods for integrating single-cell data and genetics to understand inflammatory disease complexity.docx by Hope A. Townsend (12283067)

“…First, we applied and compared the results of three recent algorithms, based on pathways (scGWAS), single-cell disease scores (scDRS), or both (scPagwas), according to accuracy/sensitivity and interpretability. …”

Mean squared Error on all unseen data. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

A. Scatter plot of the training set data before batch correction; B: Scatter plot of the training set data after batch correction. by Min-xiao Wang (20868922)

Data Sheet 1_Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.csv by Bo Lu (241075)

“…</p>Methods<p>This study utilized crowdsourced exercise walking data and incorporated diverse campus characteristics to construct a multidimensional variable system. …”

Data Sheet 2_Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.csv by Bo Lu (241075)

“…</p>Methods<p>This study utilized crowdsourced exercise walking data and incorporated diverse campus characteristics to construct a multidimensional variable system. …”

Range of point clouds. by Xinpeng Yao (18882573)

“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”

Results of ablation experiment. by Xinpeng Yao (18882573)

“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”

Transformer Encoder network structure. by Xinpeng Yao (18882573)

“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”

Line chart of frame rate. by Xinpeng Yao (18882573)

“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”

The total loss and three-component loss. by Xinpeng Yao (18882573)

“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”

Improved upsampling module based on Transformer. by Xinpeng Yao (18882573)

“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”

R project including metadata update. by Frederik Stein (22146203)

“…These problems appear to stem from both algorithmic limitations and deficiencies in submission and post-submission processes. …”

Classes of errors and gaps in BOLD metadata. by Frederik Stein (22146203)

“…These problems appear to stem from both algorithmic limitations and deficiencies in submission and post-submission processes. …”

XAFS-spectra of the reference substances by Sebastian Praetz (6576515)

Design of stiffened panels for stress and buckling via topology optimization: data by Sheng Chu (19655605)

“…[figure number].xlsk</p><p>It gives the data of convergence history, i.e., Fig. 13.xlsk provides the data of convergence history curves shown in Fig. 13.…”

A collection of visual features and their extremes. by Hector Torres (11708207)

“…<p>This figure illustrates different visual elements assessed by the M.E.D.V.I.S. algorithm, along with examples representing the two ends of each spectrum. …”