Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.

Last update: Jan 01, 2022

Overview

Cancer-and-Tumor-Detection-Using-Inception-model

In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.

Model Chosen - Inception V3 Architecture

Localisation example

Notebook contains text that guides through the project.

Thank you.

Owner

Deepak Nandwani

A Machine Learning and Data Science Engineer, my goal is to make a +ve impact on millions of people's daily lives & to be hyper-optimistic about the future.

GitHub Repository

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Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.

Related tags

Overview

Cancer-and-Tumor-Detection-Using-Inception-model

Model Chosen - Inception V3 Architecture

Localisation example

Thank you.

Owner

Deepak Nandwani

PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems

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Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.

Related tags

Overview

Cancer-and-Tumor-Detection-Using-Inception-model

Model Chosen - Inception V3 Architecture

Localisation example

Thank you.

Owner

Deepak Nandwani

PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems

This toolkit provides codes to download and pre-process the SLUE datasets, train the baseline models, and evaluate SLUE tasks.

Simple implementation of OpenAI CLIP model in PyTorch.

UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring

Unofficial implementation of Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation

This is the implementation of GGHL (A General Gaussian Heatmap Labeling for Arbitrary-Oriented Object Detection)

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

Code repo for "FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation" (ICCV 2021)

Source code for "MusCaps: Generating Captions for Music Audio" (IJCNN 2021)

This is a custom made virus code in python, using tkinter module.

MAME is a multi-purpose emulation framework.

Rendering Point Clouds with Compute Shaders

Time series annotation library.

Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer"

Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation

Multi-Anchor Active Domain Adaptation for Semantic Segmentation (ICCV 2021 Oral)

Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs

Mini-hmc-jax - A simple implementation of Hamiltonian Monte Carlo in JAX

A little Python application to auto tag your photos with the power of machine learning.

This is an official implementation for "PlaneRecNet".

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long, Evan Shelhamer, and Trevor Darrell. CVPR 2015 and PAMI 2016.