🐾 Training a machine learning model to recognize 15 different animal classes and classify images accordingly.
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Updated
May 31, 2024 - Python
🐾 Training a machine learning model to recognize 15 different animal classes and classify images accordingly.
🧠 A deep learning model that classifies brain images as either having a tumor or not.
Visualization of 1D CNNs filters space for Time Series Analysis
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
UDS (Udacity Driverless System) is an autonomous driving project developed using deep learning techniques and socket communication with a simulator. It was developed as an internship project during my internship at Zhilin Information Technology Co., Ltd., organized by Taiyuan University of Technology and the company itself, in 10.04.2024-23.04.2024
Optmization of the U-Net-based heart sound segmentation model for FPGA implementation
This is a personal project implementing Convolutional Neural Networks (CNNs) and Variational Autoencoder (VAE) for sound generations
pip install antialiased-cnns to improve stability and accuracy
ITrans: Generative Image Inpainting with Transformers, ChinaMM 2023, Multimedia Systems
🦖Pytorch implementation of popular Attention Mechanisms, Vision Transformers, MLP-Like models and CNNs.🔥🔥🔥
E(2)-Equivariant CNNs Library for Pytorch
A set of experiments inspired by the paper "Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs" by Jonathan Frankle, David J. Schwab, Ari S. Morcos
Deploy CNNs model with four FLIR camera synchronously streaming target image
Visualization methods to interpret CNNs and Vision Transformers, trained in a supervised or self-supervised way. The methods are based on CAM or on the attention mechanism of Transformers. The results are evaluated qualitatively and quantitatively.
several basic neural networks[mlp, autoencoder, CNNs, recurrentNN, recursiveNN] implements under several NN frameworks[ tensorflow, pytorch, theano, keras]
A Novel Approach to Video Super-Resolution using Frame Recurrence and Generative Adversarial Networks | Python3 | PyTorch | OpenCV2 | GANs | CNNs
CNNs for CIFAR10 (TensorFlow 2)
ConvNeXt conversion code for PT to TF along with evaluation code on ImageNet-1k val.
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