This repository contains the MATLAB library implementing the data fusion algorithm. It is associated to the article "Synthesizing developmental trajectories by semi-supervised learning", Villoutreix P., Andén J., et al., 2017.

decision-level-data-fusion-of-image-and-speech-recognition-system

“Detecting an object in an area based on the command given through speech using MFCC and HMM for Speech \& HOG and SVM for Image as Features and classifier respectively”

deeplearning-models

A collection of various deep learning architectures, models, and tips

demo_for_kalmanfilter

fusion location with only ranging and 6-axis imu sensor in similink data

examples

Home for Elasticsearch examples available to everyone. It's a great way to get started.

extendedobjecttracking

Sensor Data Fusion Group

external-attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

feature-engineering-for-ml-zh

:book: [译] 面向机器学习的特征工程

feature-level-fusion-of-palm-print-and-palm-vein

Biometric systems have become a major part of research due its application of identification. Code provides a multimodal biometric system using palm prints modality combined with palm print modality. DCT transformation is applied initially into input image. The proposed methodology uses standard deviation of pre-defined block of DCT coefficient as feature vector. In this way single image is converted into feature vector of 1 x 39. Recognition process is being done by performing distance measurement between feature vector of testing and training data set. Results show that the False Acceptance Rate (FAR) of feature level fusion is less than that of uni-modal systems, hence having multimodality is advantageous. Testing and training is done on database of 500 students of College of Engineering Pune, Pune, India. Canberra distance shows best result when compared to Euclidean or Manhatten distance.

few-shot

Repository for few-shot learning machine learning projects

fourier-transform-via-kalman-filter

This is an attempt to perform data fusion in frequency domain using Kalman Filter

fusion-maps-analyzer-matlab

Simple implementation of the distributed cognitive maps for environment interpretation. Use artificial data selected / given by user. The input activity mildly influences the belief of the cortically inspired relaxation network. The network dynamics ensures convergence to a stable state in which all quantities are in agreement given the mathematical constraints. Matlab version for easy prototyping and parametrisation.

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