Graphical representation of KerTAD algorithm. by Luka Maisuradze (8791229)

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. …”

Input gene scores. by Sergio Picart-Armada (4666903)

An overview of our ceRNAR package. by Yi-Wen Hsiao (13767916)

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

Recognition of each neuron’s digital identity. by Yuxiang Wu (748543)

Illustration of the steps used to construct the mask for identifying corner regions in Hi-C maps. by Luka Maisuradze (8791229)

Schematic overview of SINATRA Pro: A novel framework for discovering biophysical signatures that differentiate classes of proteins. by Wai Shing Tang (9541179)

Data generation process. by Nicola Dietler (12551766)

Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction by Raul A. Flores (2910539)

“…Machine-learning-based surrogate models have the potential to accelerate the search for polymorphs that target specific applications. Herein, we report a readily generalizable active-learning (AL) accelerated algorithm for identification of electrochemically stable iridium oxide polymorphs of IrO₂ and IrO₃. …”

Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data by Lijia Wang (314011)

“…<a href="https://doi.org/10.1080/01621459.2023.2270657" target="_blank">Supplementary materials</a> for this article are available online.…”

Trained Model by TAPAS CHAKRABORTY (10923396)

“…Accurate prediction of these interactions is vital for drug design, target identification, and understanding disease progression. …”

An AI-based Ecosystem for Real-time Gravitational Wave Analyses by Erik Katsavounidis (19369348)

“…These searches include A-frame, a low-latency machine learning pipeline for compact binary sources of gravitational waves, DeepClean, a deep learning-based denoising scheme for astrophysical gravitational waves, GWAK, a semi-supervised AI strategy to identify unmodeled gravitational wave transients, and AMPLFI, a pipeline for deep learning-based parameter estimation, leading to latency improvements for multi-messenger targets. …”

Raw LC-MS/MS and RNA-Seq Mitochondria data by Stefano Martellucci (16284377)

“…The results were subsequently processed to filter out common contaminants, decoy hits from the reverse database, and protein groups identified by a single peptide. The data were filtered as follows: (a) binary expression of a protein (i.e., protein exclusively identified in either scLRP1+/+ or scLRP1-/-) was only considered relevant if all scLRP1+/+ samples or all scLRP1-/- samples expressed the protein. …”