Popular GitHub Repositories for Rf Signals

RF-DETR is a real-time object detection model architecture developed by Roboflow, released under the Apache 2.0 license.

LiveStore is a next-generation state management framework based on reactive SQLite and built-in sync engine.

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

Unsupervised time series anomaly detection library

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

Deep learning software to decode EEG, ECG or MEG signals

Training neural models with structured signals.

? LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). ? Extracts signals from prompts & responses, ensuring safety & security. ?? Features include text quality, relevance metrics, & sentiment analysis. ? A comprehensive tool for LLM observability. ?

INTERSPEECH 2023-2024 Papers: A complete collection of influential and exciting research papers from the INTERSPEECH 2023-24 conference. Explore the latest advances in speech and language processing. Code included. Star the repository to support the advancement of speech technology!

Code for SuDoRm-Rf networks for efficient audio source separation. SuDoRm-Rf stands for SUccessive DOwnsampling and Resampling of Multi-Resolution Features which enables a more efficient way of separating sources from mixtures.

i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (channel attention) and *temporal dimension*. iii. Common spatial pattern (CSP), an efficient feature enhancement method, realized with Python.

ECG classification programs based on ML/DL methods

PyTorch implementation of VQ-VAE + WaveNet by [Chorowski et al., 2019] and VQ-VAE on speech signals by [van den Oord et al., 2017]

code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"

We have used Deep Reinforcement Learning and Advanced Computer Vision techniques to for the creation of Smart Traffic Signals for Indian Roads. We have created the scripts for using SUMO as our environment for deploying all our RL models.

remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN), and Long Short Term Memory (LSTM) unit

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals. WSDM 2021.

Implementation of BEST-RQ - a model for self-supervised learning of speech signals using a random projection quantizer, in Pytorch.

(ICLR'25) PaPaGei: Open Foundation Models for Optical Physiological Signals