Brinkley97

Brinkley97's Stars

• langendorfr/netcom

  An R package to infer system functioning by empirically comparing networks to each other.

  Language:R5

• ryanfarrell/llnl-dssi-2019-computer-vision

  Slides/Examples for LLNL Data Science Summer Institute (DSSI) Course on Computer Vision

  1

• DarianNwankwo/Multi-Fidelity-Bayesian-Optimization

  Language:Jupyter Notebook1

• joao-nunes/spiking-neural-networks-a-survey

  Oficial repository of the paper "Spiking Neural Networks: A Survey" by João Nunes, Marcelo Carvalho, Diogo Carneiro, and Jaime S. Cardoso

  Language:Python6

• curiousily/Machine-Learning-from-Scratch

  Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

  Language:Jupyter Notebook16565

• HazyResearch/spacetime

  Code for SpaceTime 🌌⏱️. Proposed in Effectively Modeling Time Series with Simple Discrete State Spaces, ICLR 2023.

  Language:Python15920

• thearn/webcam-pulse-detector

  A python application that detects and highlights the heart-rate of an individual (using only their own webcam) in real-time.

  Language:Python3.1k594

• avinashhsinghh/Heart-Rate-Detection

  Heart Rate Detection using Web Camera

  Language:JavaScript4015

• linkedin/greykite

  A flexible, intuitive and fast forecasting library

  Language:Python1.8k104

• qiriro/PPG

  Photoplethysmogram-based Real-Time Cognitive Load Assessment Using Multi-Feature Fusion Model

  Language:Python6237

• rohintangirala/eulerian-remote-heartrate-detection

  Remote heart rate detection through Eulerian magnification of face videos

  Language:Python31452

• habom2310/Heart-rate-measurement-using-camera

  real time application to measure heart rate

  Language:Python427140

• phuselab/pyVHR

  Python framework for Virtual Heart Rate

  Language:HTML450126

• PGomes92/pyhrv

  Python toolbox for Heart Rate Variability

  Language:Python26477

• mne-tools/mne-python

  MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

  Language:Python2.7k1.3k

• McJackTang/MMPD_rPPG_dataset

  MMPD: Multi-Domain Mobile Video Physiology Dataset(EMBC2023 Oral)

  Language:Python10513

• FKgk/detect-heart-rate-using-face

  Language:Jupyter Notebook5413

• nasir6/face-segmentation

  Language:Jupyter Notebook527

• paulvangentcom/heartrate_analysis_python

  Python Heart Rate Analysis Package, for both PPG and ECG signals

  Language:Python933322

• jayantj1j/Heart-rate-estimation-from-video-using-CNN

  An attempt to measure heart rates in humans using camera-based remote photoplethysmography (RPPG) method

  Language:Jupyter Notebook103

• ZitongYu/STVEN_rPPGNet

  Main code of "Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement"

  Language:Python15444

• AiPEX-Lab/Respiratory-Rate

  Language:Python83

• mrsergazinov/gluformer

  The official implementation of the paper "Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification."

  Language:Jupyter Notebook194

• keras-team/keras

  Deep Learning for humans

  Language:Python61.6k19.4k

• kazuto1011/grad-cam-pytorch

  PyTorch re-implementation of Grad-CAM (+ vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps)

  Language:Python783174

• jacobgil/pytorch-grad-cam

  Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

  Language:Python10.2k1.5k

• vickyliin/gradcam_plus_plus-pytorch

  A Simple pytorch implementation of GradCAM and GradCAM++

  Language:Jupyter Notebook8423

• lpphd/multivariate-attention-tcn

  Language:Jupyter Notebook8917

• igfox/multi-output-glucose-forecasting

  The code used for the paper Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories published in KDD 2018

  Language:Python4810

• MLD3/Deep-Residual-Time-Series-Forecasting

  Implementation of architecture for 2020 OhioT1D competition submission. Includes weights from pre-training runs with Tidepool data set. Baseline architecture is N-BEATS, modifications include RNN/shared output blocks, additional Losses. https://folk.idi.ntnu.no/kerstinb/kdh/KDH_ECAI_2020_Proceedings.pdf

  Language:Python92