lodeguns
AI Researcher specialized in neuromorphic and deep learning models, X-AI, music generative systems.
University of SalernoSalerno
Pinned Repositories
BioSemanticTechII
Some relevant examples of bio medical semantic-web leveraging R, SPARQL querying PubMed and MeSH
Cross-X-AI
Cross X-AI: Explainable semantic segmentation of laparoscopic images in relation with depth estimations.
Elegans-AI-Artificial-Connectomic-Networks
This is the repository of the journal paper Elegans-AI: how the connectome of a living organism could model artificial neural networks. Bardozzo et al.
fatigue
This is the repository of the journal paper: Neural networks for fatigue crack propagation predictions in real-time under uncertainty - Giannella et al.
FuzzyAdaptiveBinarization
This is the repository of the journal paper: Sugeno integral generalization applied to improve adaptive image binarization. Bardozzo et al.
salina_a2c_gym_anytrading
Slight modification to one of the Facebook Salina examples, to test the A2C algorithm on financial series.
Solids-classification-3D-CNN-3D-GradCam
Here we introduce the problem of 3D solids classification with a CNN (spheres and octahedra). We implemented a 3D GradCam model, in order to underline the most relevant 3D volumes useful for classification.
StaSiS-Net
This is the repository of the journal paper: StaSiS-Net: a stacked and siamese stereo network for depth reconstruction in modern 3D laparoscopy. Bardozzo et al.
VTK-OBJ
From VTK to OBJ wavefront converter
ZED-3D-Aruco
This is a simple example where the 3D reconstruction through ZED sdk is combined with the aruco markers detection.
lodeguns's Repositories
lodeguns/VTK-OBJ
From VTK to OBJ wavefront converter
lodeguns/StaSiS-Net
This is the repository of the journal paper: StaSiS-Net: a stacked and siamese stereo network for depth reconstruction in modern 3D laparoscopy. Bardozzo et al.
lodeguns/Solids-classification-3D-CNN-3D-GradCam
Here we introduce the problem of 3D solids classification with a CNN (spheres and octahedra). We implemented a 3D GradCam model, in order to underline the most relevant 3D volumes useful for classification.
lodeguns/salina_a2c_gym_anytrading
Slight modification to one of the Facebook Salina examples, to test the A2C algorithm on financial series.
lodeguns/BioSemanticTechII
Some relevant examples of bio medical semantic-web leveraging R, SPARQL querying PubMed and MeSH
lodeguns/ZED-3D-Aruco
This is a simple example where the 3D reconstruction through ZED sdk is combined with the aruco markers detection.
lodeguns/Cross-X-AI
Cross X-AI: Explainable semantic segmentation of laparoscopic images in relation with depth estimations.
lodeguns/CustomLayers-in-Tensorflow-2.0
The script below shows how to modify, with a customized layer, the value of the tensors of a network being trained. This behaviour is modelled considering static and dynamic operation assignments. The layout is written with the new version of Tensorflow 2.0 and Keras 2.3.0 Cublas 10, Cudnn 7.
lodeguns/FuzzyAdaptiveBinarization
This is the repository of the journal paper: Sugeno integral generalization applied to improve adaptive image binarization. Bardozzo et al.
lodeguns/Java-COOL-Compiler-
Java Lexer, Parser, Seman and CGEN for the COOL language.
lodeguns/BioSemanticTech
Some documented examples of bio semantic-web technologies in R, XSLT and SPRQL
lodeguns/LSTM-course-May
Didattic Material for the LSTM workshop done the 23-25 May 2018 @ unisa.
lodeguns/Elegans-AI-Artificial-Connectomic-Networks
This is the repository of the journal paper Elegans-AI: how the connectome of a living organism could model artificial neural networks. Bardozzo et al.
lodeguns/fatigue
This is the repository of the journal paper: Neural networks for fatigue crack propagation predictions in real-time under uncertainty - Giannella et al.
lodeguns/meta-analysis-logistic-regression-with-BUGS
lodeguns/MOOs-An
Multi Omic Oscillations Patterns Analyses
lodeguns/MORA
A study on multi-omic oscillations in Escherichia coli metabolic networks. Journal paper.
lodeguns/Multi-omicSignals
This repository contains the supplementary materials of the manuscript mentioned in the title, and associated source code, the whole data set of signals and some functions to obtain fast results with several multi-omic combinations within and between bacteria. Should you need help running our code, please contact us.
lodeguns/NetBasAdj
Metabolic Networks Based Adjacency for Multi Omic Patterns Analyses