Keras
Showing 36 of 87 projects
A Siamese neural network for LiDAR-based loop closing and localization by predicting scan overlap and relative yaw angle.
A TensorFlow library for training, serving, and interpreting decision forest models like Random Forests and Gradient Boosted Trees.
A modular deep reinforcement learning framework for portfolio management, enabling algorithmic stock trading with DQN and DDPG agents.
A deep learning system that classifies food images into 230 categories and retrieves matching recipes using convolutional neural networks.
A quantization extension for Keras that provides drop-in replacement layers for creating quantized deep learning models in TensorFlow.
A simplified Keras-like framework for PyTorch that reduces boilerplate code for training neural networks.
A real-time dashboard for monitoring Keras model training and evaluation metrics in your browser.
An AI-powered captcha solver using SimGAN to generate synthetic training data without manual labeling.
A comprehensive Jupyter notebook tutorial covering computer vision and machine learning basics using OpenCV and Keras in Python.
A collection of deep learning tutorials and implementations using Keras and Lasagne, with a focus on Theano-based frameworks.
Trading Environment(OpenAI Gym) + DDQN (Keras-RL)
A Ruby gem providing TensorFlow bindings for basic tensor operations and machine learning tasks.
A neural networks toolbox for medical image analysis, providing specialized layers, models, and utilities for TensorFlow/Keras.
Predicts Bitcoin price trends using an LSTM-RNN with technical indicators for automated trading via the Binance API.
A Python toolbox for content-aware restoration of fluorescence microscopy images using deep learning.
Deep learning model using convolutional neural networks to predict drug-target binding affinity from protein sequences and compound SMILES.
A convolutional neural network for CAPTCHA recognition using Keras and PyTorch.
FLAME dataset and deep learning models for fire detection in aerial imagery using UAVs, supporting classification and segmentation tasks.
A Python library for stacked generalization (ensemble learning) that supports scikit-learn, XGBoost, and Keras models with out-of-fold prediction saving.
A Python-based CAPTCHA breaking solution using Keras and OpenCV, developed for a data science competition.
A semi-automated pipeline for instance-aware cell segmentation, tracking, and migration analysis in phase contrast microscopy using Mask R-CNN.
A convolutional neural network model built with Keras for recognizing captcha images generated by the Laravel Captcha library.
A Keras implementation of Microsoft's R-NET neural network for question answering on the SQuAD dataset.
A deep learning model that classifies sounds in 10-second audio clips into 527 categories from the AudioSet ontology.
An open-source starter solution for the Kaggle Toxic Comment Classification Challenge, providing ready-to-use machine learning pipelines for detecting online harassment.
Keras implementation of Pix2pix for image-to-image translation using conditional adversarial networks.
A lightweight Python library for building reproducible machine learning pipelines with minimal interface constraints.
A method for selecting interpretable feature subsets from complex models using mutual information optimization.
A collection of Google Colab tutorials teaching biologists how to apply deep learning with Keras to real-world biological and agricultural problems.
A tutorial and demo using Hyperopt to auto-optimize CNN architecture and hyperparameters for the CIFAR-100 dataset with Keras/TensorFlow.
A Keras implementation of Ladder Networks for semi-supervised learning, achieving 98% accuracy on MNIST with only 100 labeled examples.
A Delphi/Pascal binding for TensorFlow and Keras that enables Pascal developers to build, train, and deploy machine learning models.
A curated archive of pre-trained computer vision models for object detection, face recognition, fire detection, and more.
A TensorFlow/Keras LSTM model for hourly weather forecasting, offering univariate, multivariate, and multistep prediction modes.
Code for the Kaggle Dogs vs. Cats image classification competition using deep learning.
A high-level neural networks API for Delphi, written in Pascal with Python binding and support for TensorFlow, CNTK, or Theano backends.
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