# Senses-speckle [Remote Photonic Detection of Human Senses Using Secondary Speckle Patterns](https://doi.org/10.21203/rs.3.rs-724587/v1) paper Python implementation ### Abstract Neural activity research has recently gained signicant attention due to its association with sensory information and behavior control. However, current methods of brain activity sensing require expensive equipment and physical contact with the subject. We propose a novel photonic-based method for remote detection of human senses. Physiological processes associated with hemodynamic activity due to activation of the cerebral cortex affected by different senses have been detected by remote monitoring of nano‐vibrations generated due to the transient blood ow to specic regions of the brain. We have found that combination of defocused, self‐ interference random speckle patterns with a spatiotemporal analysis using Deep Neural Network (DNN) allows associating between the activated sense and the seemingly random speckle patterns. ### Experimental setup  ### Model
Optical machine for senses sensing using speckle and deep learning
Overview
Owner
Zeev Kalyuzhner
Unofficial Tensorflow Implementation of ConvNeXt from A ConvNet for the 2020s
Tensorflow Implementation of "A ConvNet for the 2020s" This is the unofficial Tensorflow Implementation of ConvNeXt from "A ConvNet for the 2020s" pap
WRENCH: Weak supeRvision bENCHmark
🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development
DeepLab-ResNet rebuilt in TensorFlow
DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Fr
A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering.
DeepFilterNet A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering. libDF contains Rust code used for dat
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.
collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do
Code for 2021 NeurIPS --- Towards Multi-Grained Explainability for Graph Neural Networks
ReFine: Multi-Grained Explainability for GNNs This is the official code for Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 20
This repository contains code to run experiments in the paper "Signal Strength and Noise Drive Feature Preference in CNN Image Classifiers."
Signal Strength and Noise Drive Feature Preference in CNN Image Classifiers This repository contains code to run experiments in the paper "Signal Stre
Aerial Imagery dataset for fire detection: classification and segmentation (Unmanned Aerial Vehicle (UAV))
Aerial Imagery dataset for fire detection: classification and segmentation using Unmanned Aerial Vehicle (UAV) Title FLAME (Fire Luminosity Airborne-b
Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network
Leaded Gradient Method (LGM) This repository contains the PyTorch implementation for paper Dynamics-aware Adversarial Attack of 3D Sparse Convolution
An addon uses SMPL's poses and global translation to drive cartoon character in Blender.
Blender addon for driving character The addon drives the cartoon character by passing SMPL's poses and global translation into model's armature in Ble
Implementation of Feedback Transformer in Pytorch
Feedback Transformer - Pytorch Simple implementation of Feedback Transformer in Pytorch. They improve on Transformer-XL by having each token have acce
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code
sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ
Code for "Long Range Probabilistic Forecasting in Time-Series using High Order Statistics"
Long Range Probabilistic Forecasting in Time-Series using High Order Statistics This is the code produced as part of the paper Long Range Probabilisti
Classification Modeling: Probability of Default
Credit Risk Modeling in Python Introduction: If you've ever applied for a credit card or loan, you know that financial firms process your information
SphereFace: Deep Hypersphere Embedding for Face Recognition
SphereFace: Deep Hypersphere Embedding for Face Recognition By Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj and Le Song License SphereFa
DiffQ performs differentiable quantization using pseudo quantization noise. It can automatically tune the number of bits used per weight or group of weights, in order to achieve a given trade-off between model size and accuracy.
Differentiable Model Compression via Pseudo Quantization Noise DiffQ performs differentiable quantization using pseudo quantization noise. It can auto
FIRA: Fine-Grained Graph-Based Code Change Representation for Automated Commit Message Generation
FIRA is a learning-based commit message generation approach, which first represents code changes via fine-grained graphs and then learns to generate commit messages automatically.
Self-Supervised Image Denoising via Iterative Data Refinement
Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S
🔮 Execution time predictions for deep neural network training iterations across different GPUs.
Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's
Official implementation of VQ-Diffusion
Vector Quantized Diffusion Model for Text-to-Image Synthesis Overview This is the official repo for the paper: [Vector Quantized Diffusion Model for T