aminul-huq

Abnormality-Corn-ISVC-23

Adversarial-Attacks

Adversarial Attacks testing on DNN models

Adversarial-Examples-For-Audio-Data

Repo for papers to read on adversarial attack and defense techniques in the audio domain.

CNN-RNN-for-Multiclass-Classification-on-SST-dataset

PyTorch implementation of multi-class sentiment classification on SST dataset using CNN and RNN.

CVAE_pytorch

CVAE implementation on MNIST dataset using PyTorch

DeepFool

PyTorch implementation of DeepFool adversarial attack.

nitrogen-deficiency-corn

Speech-Command-Classification

Speech command classification on Speech-Command v0.02 dataset using PyTorch and torchaudio. In this example, three models have been trained using the raw signal waveforms, MFCC features and MelSpectogram features.

Speech_Command_Recognition

Multi-class classification of speech command data. Dataset collected from kaggle speech recognition challenge and used pyTorch for implementation.

WideResNet_MNIST_Adversarial_Training

WideResNet implementation on MNIST dataset. FGSM and PGD adversarial attacks on standard training, PGD adversarial training, and Feature Scattering adversarial training.

aminul-huq/Adversarial-Examples-For-Audio-Data

Repo for papers to read on adversarial attack and defense techniques in the audio domain.

aminul-huq/Speech-Command-Classification

Speech command classification on Speech-Command v0.02 dataset using PyTorch and torchaudio. In this example, three models have been trained using the raw signal waveforms, MFCC features and MelSpectogram features.

aminul-huq/WideResNet_MNIST_Adversarial_Training

WideResNet implementation on MNIST dataset. FGSM and PGD adversarial attacks on standard training, PGD adversarial training, and Feature Scattering adversarial training.

aminul-huq/Abnormality-Corn-ISVC-23

aminul-huq/nitrogen-deficiency-corn

aminul-huq/Speech_Command_Recognition

Multi-class classification of speech command data. Dataset collected from kaggle speech recognition challenge and used pyTorch for implementation.

aminul-huq/AllWeights

aminul-huq/Aminul-Huq

aminul-huq/CVAE_pytorch

CVAE implementation on MNIST dataset using PyTorch

aminul-huq/aminul-huq.github.io

aminul-huq/aminulhuq

aminul-huq/Autoencoders

aminul-huq/corn_data_gen

aminul-huq/CS791_IDS

aminul-huq/CS791_LLM

Related to final course project on using LLMs

aminul-huq/cs791_project

aminul-huq/gitsub

aminul-huq/Grad-778

aminul-huq/Latex_docs_sample

This repo contains sample documents which have been created using Latex

aminul-huq/mammogram_classification

aminul-huq/medium

Implementations for the medium blog

aminul-huq/mixPGD

aminul-huq/MTL

aminul-huq/Outlier-Detection-Based-Malaria-Cell-Image-Classification

aminul-huq/python_for_image_processing_APEER

https://www.youtube.com/playlist?list=PLHae9ggVvqPgyRQQOtENr6hK0m1UquGaG

aminul-huq/THU--ACM_2019-2021

Outline of course works for the Tsinghua Masters in Advanced Computing

aminul-huq/transfer_learning

aminul-huq/Upside-Down-Classification

aminul-huq/vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

aminul-huq/WSBIM2243---Mammography-processing

We present methods to preprocess, detect tumours and segment malignant masses for the INbreast dataset.