Stunting final dataset. by Alemu Birara Zemariam (17540938)

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System architecture of this study. by Mahade Hasan (20536430)

“…Our approach involved feature selection techniques to identify the most relevant predictors, aimed at refining the models to enhance both performance and interpretability. …”

<b>A study on an efficient citrus Huanglong disease detection algorithm based on three-channel aggregated attention</b> by yizong wang (20387247)

“…Experimental results demonstrate that on a dataset comprising 12 diseases and 2 healthy states, the mean Average Precision at IoU 0.50 (mAP50) of this model achieved 97%, with a Precision of 91.5%; these figures reflect improvements of 1.1% and 1.2%, respectively, compared to the original YOLOv8 algorithm. Additionally, the inference speed increased by 14.6%, fully meeting the real-time requirements for detecting diseases in citrus fields and illustrating the effectiveness and advanced nature of the improved algorithm, thereby providing robust support for the rapid identification of diseases in the citrus cultivation process.…”

Combined dataset immune infiltration analysis by CIBERSORT algorithm. by Binming Qiu (22648115)

Results of pseudo-coloring algorithms for a normal thermogram of an individual: original gray-level image, and its pseudo-colorized images in the HSI color space under various cond... by Hamed Khodadadi (21446172)

Data and code from: AI-based image profiling and detection for the beetle byte quintet using Vision Transformer (ViT) in advanced stored product infestation monitoring by Alison Gerken (17362585)

Data Sheet 1_Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.pdf by Habtamu Setegn Ngusie (12178327)

Data Sheet 2_Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.pdf by Habtamu Setegn Ngusie (12178327)

Study flow diagram. by Shahrokh Mousavi (21989418)

“…We aimed to develop machine learning-based models using multiple algorithms to predict and identify the predictors of angina pectoris in an elderly community-dwelling population.…”

Graph representation of all possible , where <i>A</i>⁺ is constrained to be an optimal solution for the example in Fig 1. by Jordan Moutet (21800145)

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A depiction of the labeled gaps constructed by the bottom-up phase on the input shown in Fig 1. by Jordan Moutet (21800145)

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Depiction of how the label of is assigned as a function of whether are identical (row =), nested (rows ), or partially overlapping (row “else”), and as a function of the labels of... by Jordan Moutet (21800145)

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A sequence of intermediate solutions produced by the top-down phase on the input of Fig 1, leading to an optimal solution (step 5). by Jordan Moutet (21800145)

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Example input of the DPP: a phylogenetic tree T and an alignment A for L(T). by Jordan Moutet (21800145)

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(Right:) A candidate solution <i>A</i>⁺ for the example in Fig 1. by Jordan Moutet (21800145)

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Experiment on the two OrthoMaM amino acid alignments datasets. For each dataset, we show the total number of sites with gaps (across 15,868 alignments), and the percentages of thes... by Jordan Moutet (21800145)

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An optimal solution <i>A</i>⁺ for the example in Fig 1, found following the steps detailed in Fig 4. by Jordan Moutet (21800145)

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Graph representation of all possible , where <i>A</i>⁺ is constrained to be an optimal solution for the example in Fig 1. by Jordan Moutet (21800145)

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An instance of the DPP that provides a solution of the first half of the IPP problem in Fig 8. by Jordan Moutet (21800145)

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Monotone Cubic B-Splines with a Neural-Network Generator by Lijun Wang (176511)