D

deep learning

PDE-based Group Equivariant CNNs for PyTorch

Sistema de inteligencia artificial basado en visión por computadora para la detección y segmentación de latas y botellas

Practical tasks on Deep Learning (DL) and Neural Networks. 🤖

Fundamental theory and practice in Machine Learning (ML) and Data Science. 🧮

Predicting pathogenic potentials of short DNA reads with reverse-complement deep neural networks.

Webpage for the L52+ lab

This project is a re-implementation of FeatureNet using Tensorflow 2. With working segmentation code.

FakET: Simulating Cryo-Electron Tomograms with Neural Style Transfer

This repo will have all resources, labs, data which I use/d on Kaggle Network

Este proyecto es material de la materia optativa "Fundamentos Matemáticos del Aprendizaje Profundo" dictada por el Departamento de Matemática de la Facultad de Ciencias Exactas y Naturales de la Universidad de Buenos Aires

Benchmarking framework for machine learning with fNIRS

https://doi.org/10.3389/fnrgo.2023.994969

This code tries to answer the questions: what are the hardest categories to classify in both single label and multi label image classification tasks? Why do these categories present greater difficulty? Could data augmentation change which the worst performing classes are? Are there consistent patterns across both tasks that explain the poorest performing classes? By using LeNet-5, ResNet-18 and DINO ViT deep learning model architectures

Repository of real applications of neural networks coded in Python with TensorFlow/Keras and PyTorch.

This is an implementation of a very simple neural network from scratch.

This project provides a deep learning approach to learn machining features from CAD models using a hierarchical graph convolutional neural network.

Protocol for network and expression integration to identify potential defense gene in host-pathogen interactions