DataSheet1_NeuroPack: An Algorithm-Level Python-Based Simulator for Memristor-Empowered Neuro-Inspired Computing.ZIP by Jinqi Huang (12433320)

“…In this study, we present NeuroPack, a modular, algorithm-level Python-based simulation platform that can support studies of memristor neuro-inspired architectures for performing online learning or offline classification. …”

Analysis the performance scores of the RNN-based clone detection techniques in detecting of Type-III and Type-IV clones. by Fahmi H. Quradaa (17896527)

Design and Implementation of a Browser-Based Toolfor Protecting Gaming Assets from UnauthorizedAccess by Alim Imashev (22606007)

“…<p dir="ltr">The project <b>“Design and Implementation of a Browser-Based Tool for Protecting Gaming Assets from Unauthorized Access”</b> focuses on developing a security-oriented software solution that safeguards digital game assets within browser environments.…”

The general structure of the BCI model and simulation results of BCI Toolbox. by Haocheng Zhu (8982086)

Supporting data for "Interpreting complex ecological patterns and processes across differentscales using Artificial Intelligence" by Yifei Gu (9507104)

“…</p><p dir="ltr">Firstly, a Python package HSC3D, was developed to quantify habitat structural complexity (HSC) at the community level. …”

FPR and FNR analysis based on different time steps. by Mohanad Faeq Ali (21354273)

Data_Sheet_1_oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data.pdf by Tung Dang (15229042)

“…Here, we introduce an efficient and high-performance decoding package incorporating a forward variable selection (FVS) algorithm and hyper-parameter optimization that automatically identifies the best feature pairs for both classification and regression models, where a total of 18 ML models are implemented by default. First, the FVS algorithm evaluates the goodness-of-fit across different models using the k-fold cross-validation step that identifies the best subset of features based on a predefined criterion for each model. …”

Table_2_XCast: A python climate forecasting toolkit.docx by Kyle Joseph Chen Hall (13049001)

“…XCast, an Xarray-based climate forecasting Python library developed by the authors, bridges this gap. …”

Table_1_XCast: A python climate forecasting toolkit.docx by Kyle Joseph Chen Hall (13049001)

“…XCast, an Xarray-based climate forecasting Python library developed by the authors, bridges this gap. …”

Table_2_XCast: A python climate forecasting toolkit.docx by Kyle Joseph Chen Hall (13049001)

“…XCast, an Xarray-based climate forecasting Python library developed by the authors, bridges this gap. …”

Table_1_XCast: A python climate forecasting toolkit.docx by Kyle Joseph Chen Hall (13049001)

“…XCast, an Xarray-based climate forecasting Python library developed by the authors, bridges this gap. …”

FPR and FNR analysis based on varying cyber attack types. by Mohanad Faeq Ali (21354273)

Quanfima: An open source Python package for automated fiber analysis of biomaterials by Roman Shkarin (6580823)

“…Due to the demand for reproducible science with Jupyter notebooks and the broad use of the Python programming language, we have developed the new Python package quanfima offering a complete analysis of hybrid biomaterials, that include the determination of fiber orientation, fiber and/or particle diameter and porosity. …”

Parallel plot showing hyperparameter exploration. by Ramona Leenings (11167294)

napari-superres: an open-source implementation of methods for Fluorescence Fluctuation-based Super-Resolution Microscopy (FF-SRM) by Rocco D'Antuono (7558739)

“…FF-SRM methods are applicable to data sets acquired with any fluorescence microscopy setup (reviewed in [1]), but have not been implemented yet in an integrated GUI: they are instead available as a multitude of scripts/software, based on Matlab [2,7], Python [3,7], and FIJI/ImageJ [2,4,5,6,7]. …”

Class architecture. by Ramona Leenings (11167294)

A workflow based on Sentinel-1 SAR data and open-source algorithms for unsupervised burned area detection in Mediterranean ecosystems by Giandomenico De Luca (11007332)

“…The entire processing workflow was developed in Python-based scripts. We analyzed two time-series covering about one month before and after the fire events and using both VH and VV polarizations for each study site. …”

The network of sequences provided by method NBVFS-CM. by László Bántay (18530067)

Subjects:

The network of sequences provided by method NBVFS-TM. by László Bántay (18530067)

Subjects:

Comparison of visualization techniques. by László Bántay (18530067)

Subjects: