Stereo-image depth reconstruction with different matching costs and matching algorithms in Python using Numpy and Numba
Embedder with binary sparse distributed representation.
Lab experiments of Soft Computing Techniques
CPU-based spiking neural network framework for classification layers employing first-spike coding and supervised STDP training.
🥇Winner Take All Hash algorithm by J. Yagnik, implemented in Python.
Two-player TicTacToe winner-takes-all with EOS stakes via smart contract
Iterative winners-take-all algorithm
A collection of artificial neuron models. Written in Julia using Jupyter Notebooks
A neuroscientific sequence learning model on spiking neural networks with winner-take-all circuits and lateral inhibition. Written using the NEST neural simulator and custom neuron/synapse models.
GUI for winner-take-all clustering implementation
Pythorch implementation of Winner-Take-All Autoencoder
MATLAB code for training and simulating the chemical-based image classification network detailed in "Leveraging autocatalytic reactions for chemical-domain image classification"
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