a graduation project
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Updated
Aug 23, 2021 - Python
a graduation project
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Implementation of a deep neural network for denoising extreme low-light images using residual learning
An exploration of recommender systems using Bayesian Bandit, matrix factorization, deep learning, and residual learning.
Offical implementation of "Advancing Spiking Neural Networks towards Deep Residual Learning" (IEEE TNNLS 2024)
Deep Spatiotemporal Clutter Filtering of Transthoracic Echocardiographic Images Using a 3D Convolutional Auto-Encoder
This repository contains a comprehensive implementation of gradient descent for linear regression, including visualizations and comparisons with ordinary least squares (OLS) regression. It also includes an additional implementation for multiple linear regression using gradient descent.
Face Template Protection Through Residual Learning Based Error-Correctinig Codes
Implement PDDLStream for Toyota Human Support Robot (HSR) and offer parallel reinforcement learning environment on Isaac Sim.
A deep neural network developed following the residual learning and separable convolution paradigms to diagnose basal and squamous cell carcinoma using a subset of ISIC dataset.
Implementation of ResNet series Algorithm
Implementation of some Neural Network architecture using Numpy, TensorFlow and Keras.
Classifying Deepfake imges using Residual learning Architecture
🧠 ResNet: Deep Residual Learning for Image Recognition
tensorflow implementation of dr2net
IDC prediction in breast cancer histopathology images using deep residual learning with an accuracy of 99.37% in a subset of images containing a total of 7,500 microscopic images.
Designed a smaller architecture implemented from the paper Deep Residual Learning for Image Recognition and achieved 93.65% accuracy.
Official implementation of TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testing (MIDL 2022)
Residual Embedding Similarity-based Network Selection (RESNets) for forecasting network dynamics.
[ICCV W] Contextual Convolutional Neural Networks (https://arxiv.org/pdf/2108.07387.pdf)
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