openalexZenodo (CERN European Organization for Nuclear Research)2026-08-12Cited by 0
Research data and code supporting "Label-free biochemical imaging and time point analysis of neural organoids via deep learning–enhanced Raman microspectroscopy"
This repository contains the datasets and source code associated with Georgiev et al., Science Advances (2026). https://doi.org/10.1126/sciadv.aec5080 To get started with the software, visit our GitHub repository. The software provides both a graphical user interface (GUI) and a command-line interface (CLI) for running the analysis pipeline.
Abstract The rapid growth of big data and the increasing complexity of deep learning applications have created significant challenges for traditional data processing infrastructures, particularly in terms of scalability, performance, and resource efficiency. This study presents a…
Modern machine learning systems are increasingly deployed in settings that require persistent interaction, adaptation, memory, and decision-making over time. Yet, most learning paradigms remove the temporal pressures faced by physically embedded agents: the world waits for comput…
Release v0.1.1 · oubino/locpix_points / oubino/locpix_points at v0.1.1 This software is for classification of point-cloud data based on the features and spatial arrangement of clusters within the data. It uses graph-based neural networks, taking the point coordinates and their as…
This record provides the processed data and Version 1.0 of the analysis code supporting the study “Enhancing Urban Flood Risk Assessment: A PCA-Integrated Deep Learning Surrogate for Hazard and Damage Prediction.” The archive includes the synthetic rainfall–inundation–damage data…
Deep Neural Networks (DNNs) exhibit acute vulnerabilities to intermediate activation layer perturbations engineered through out-of-distribution (OOD) noise injection and feature-steering gradient updates. Conventional defensive paradigms—such as adversarial retraining or external…
This study aims to evaluate the implementation of the deep learning approach in Physical Education, Sports, and Health (PJOK) learning in public junior high schools in Godean District, based on the Countenance Stake Evaluation Model, which includes antecedents, transactions, and…