Attentional Focus Modulates Automatic Finger‑tapping Movements

Related tags

Deep LearningAFM
Overview

AFM

Xilei Zhang, Xingxun Jiang, Xiangyong Yuan, Wenming Zheng, "Attentional Focus Modulates Automatic Finger‑tapping Movements", in Scientific Reports, 2021

Requirements

Files and Folders

  1. model_exp1__data_exp2 && model_exp1__data_exp3

    • main_folder
      • /data2/jiangxingxun/fingerExp/confusion_matrix
    • code
      • exp2:model_1_data_2.py
      • exp3:model_1_data_3.py
    • log_folder
      • exp2:log/model_exp1__data_exp2/
      • exp3:log/model_exp1__data_exp3/
  2. part_all: part data of ex1, repeat time 10

    • main_folder
      • /data2/jiangxingxun/fingerExp/machineLearning1_copy/
    • code
      • SVM_1_rbf_change_new.py
    • log_folder
      • part_all

Cite

@article{zhang2021attentional,
  title={Attentional focus modulates automatic finger-tapping movements},
  author={Zhang, Xilei and Jiang, Xingxun and Yuan, Xiangyong and Zheng, Wenming},
  journal={Scientific Reports},
  volume={11},
  number={1},
  pages={1--13},
  year={2021},
  publisher={Nature Publishing Group}
}
Owner
Xingxun Jiang
Xingxun Jiang
Deep Halftoning with Reversible Binary Pattern

Deep Halftoning with Reversible Binary Pattern ICCV Paper | Project Website | BibTex Overview Existing halftoning algorithms usually drop colors and f

Menghan Xia 17 Nov 22, 2022
Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network

Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network The performances of tree ensemb

Mustapha Unubi Momoh 2 Sep 13, 2022
Generating Digital Painting Lighting Effects via RGB-space Geometry (SIGGRAPH2020/TOG2020)

Project PaintingLight PaintingLight is a project conducted by the Style2Paints team, aimed at finding a method to manipulate the illumination in digit

651 Dec 29, 2022
TianyuQi 10 Dec 11, 2022
CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation

CSKG: The CommonSense Knowledge Graph CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation: AT

USC ISI I2 85 Dec 12, 2022
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

MGANs Training & Testing code (torch), pre-trained models and supplementary materials for "Precomputed Real-Time Texture Synthesis with Markovian Gene

290 Nov 15, 2022
[CVPR 2022] Official Pytorch code for OW-DETR: Open-world Detection Transformer

OW-DETR: Open-world Detection Transformer (CVPR 2022) [Paper] Akshita Gupta*, Sanath Narayan*, K J Joseph, Salman Khan, Fahad Shahbaz Khan, Mubarak Sh

Akshita Gupta 127 Dec 27, 2022
Codes for “A Deeply Supervised Attention Metric-Based Network and an Open Aerial Image Dataset for Remote Sensing Change Detection”

DSAMNet The pytorch implementation for "A Deeply-supervised Attention Metric-based Network and an Open Aerial Image Dataset for Remote Sensing Change

Mengxi Liu 41 Dec 14, 2022
An ML & Correlation platform for transforming disparate data points of interest into usable intelligence.

SSIDprobeCollector An ML & Correlation platform for transforming disparate data points of interest into usable intelligence. At a High level the platf

Bill Reyor 1 Jan 30, 2022
StyleGAN2-ADA-training-jupyter - Training custom datasets in styleGAN2-ADA by NVIDIA using Jupyter

styleGAN2-ADA-training-jupyter Training custom datasets in styleGAN2-ADA on Jupyter Official StyleGAN2-ADA by NIVIDIA Paper Training Generative Advers

Mang Su Hyun 2 Feb 24, 2022
An end-to-end implementation of intent prediction with Metaflow and other cool tools

You Don't Need a Bigger Boat An end-to-end (Metaflow-based) implementation of an intent prediction flow for kids who can't MLOps good and wanna learn

Jacopo Tagliabue 614 Dec 31, 2022
A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical Reasoning

Orchard Dataset This repository contains the code used for generating the Orchard Dataset, as seen in the Multi-Hierarchical Reasoning in Sequences: S

Bill Pung 1 Jun 05, 2022
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation (CIKM'17)

RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar

Yu Zhang 5 Feb 10, 2022
Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch

Segformer - Pytorch Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch. Install $ pip install segformer-pytorch

Phil Wang 208 Dec 25, 2022
Data for "Driving the Herd: Search Engines as Content Influencers" paper

herding_data Data for "Driving the Herd: Search Engines as Content Influencers" paper Dataset description The collection contains 2250 documents, 30 i

0 Aug 17, 2021
Learning to Predict Gradients for Semi-Supervised Continual Learning

Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le

Yan Luo 2 Mar 05, 2022
Deep Learning with PyTorch made easy 🚀 !

Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c

381 Dec 22, 2022
This repository contains the entire code for our work "Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding"

Two-Timescale-DNN Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding This repository contains the entire code for our work

QiyuHu 3 Mar 07, 2022
PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"

Transparency-by-Design networks (TbD-nets) This repository contains code for replicating the experiments and visualizations from the paper Transparenc

David Mascharka 351 Nov 18, 2022
Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction".

GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear

Ursa Zrimsek 2 Dec 14, 2022