Mohd Fitri Alif Bin Mohd Kasai's repositories
DL-project
Improve CNN model using data augmentation with GAN
CNN-with-GA-Keras
2-layer Convolutional Neural Network with Genetic Algorithm (GA) implementation.
CoDeepNEAT
An implementation of CoDeepNEAT with possible extensions
computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
EEG_emotion
EEG sentiment analysis
Evolution-1
Genetic algorithm applied to a basic neural network in keras using DEAP (https://github.com/DEAP/deap)
Evolving-CNNs-using-GA
Evolving Architectures for Convolutional Neural Networks using the Genetic Algorithm
General-Advanced-Deep-Learning-Trainings
Contents, •Neural networks – Perceptron, Adaline, BP neural networks, unsupervised learning neural networks, RBF neural networks, etc. •Optimization methods – Genetic algorithms, swarm intelligence, etc. •Training deep neural networks – Parameter and structure tuning, etc. •Deep learning neural network models – Convolutional Neural Networks (CNN), autoencoders
Kaggle_digit_recognizer_with_deap
Kaggle digit recognizer with deap is an implementation of genetic algorithm that tries to optimize model produced by lenet5 using this CNN option (learning rate, batch size, receptive field etc) as hyperparameters optimized by genetic algo
Keras-CoDeepNEAT-1
CoDeepNEAT inspired implementation using Keras and Tensorflow as backend.
keras-idiomatic-programmer
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
KerasEvolution-1
NEAT-like genetic algorithm for evolving best Neural Networks for a given dataset
neat-python
A Python version of the NEAT algorithm (NeuroEvolution of Augmenting Topologies)
Neural-Architecture-Search-GA
A basic Neural Architecture Search using Multi Objective Genetic Algorithms. Hyper-parameter tuning with Genetic Algorithms. Done as part of the Artificial Intelligence course at IIIT-D
nsga-keras
evolution for NAS based on NSGA/NSGAII/NSGAIII (with parallel evaluation)
petridishnn
Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search
ResearchChatGPT
50 use cases of ChatGPT for research work
SMate--SyntheticMinorityAdversarialTechnique
The novel SMate approach leverages GAN minority-class image generators, which benefit from Transfer Learning from majority-class image generators. Consequently, SMate outperforms SMOTE for imbalanced image data-sets. Research at Stanford University, by: Pablo Rodriguez Bertorello, Liang Ping Koh
Traffic-Signal-Violation-Detection-System
A Computer Vision based Traffic Signal Violation Detection System from video footage using YOLOv3 & Tkinter. (GUI Included)
VGG16-In-Keras
Implementation of VGG16 architecture in Keras