(ICCV 2021) BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search

Building multi-input CNN for predicting the age of bones from X-Ray and gender using PyTorch.

Absolutely incredible and fresh-pressed Google Colab Notebook to train and generate Music with the SOTA GGA-MG (AR-CNN) Hybrid Neural Network (AI).

hCNN: Hybrid Neural Network (Hybrid-NN), a MATLAB NN toolbox that supports complex valued data and insertion of Signal Processing Modules.

A short-term predictive traffic model for a locality Oxford, UK was developed using a Hybrid Temporal Graph Convolutional Neural Network.

A comparison analysis between classical and quantum-classical (or hybrid) neural network and the impact effectiveness of a compound adversarial attack.

A Hybrid Nerual Network Classifier with Oversample Minority Class.

Implementation of DENFIS for predicting time-series data.

Twitter Sentiment Analysis using Deep learning models.

Kickstarter project success or failure prediction. Using Word2Vec to train embedding file.

A custom lightweight neural network that incorporates a Bag Of Visual Words model alongside a custom shallow CNN to estimate the apparent age of a face.

Sentiment Analysis of Tweets using Neural Networks with Pytorch

Hybrid neural network model is protected against adversarial attacks using either adversarial training or randomization defense techniques

Hybrid neural network is protected against adversarial attacks using various defense techniques, including input transformation, randomization, and adversarial training.

A quantum-classical (or hybrid) neural network and the use of a adversarial attack mechanism. The core libraries employed are Quantinuum pytket and pytket-qiskit. torchattacks is used for the white-box, targetted, compounded adversarial attacks.