https://github.com/baha2rm98/human_data_analytics_project
Human Data Analytics Course Project
https://github.com/baha2rm98/human_data_analytics_project
deep-convolutional-networks deep-learning inceptionv4 resnet-50
Last synced: 2 months ago
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Human Data Analytics Course Project
- Host: GitHub
- URL: https://github.com/baha2rm98/human_data_analytics_project
- Owner: Baha2rM98
- Created: 2023-02-14T11:14:25.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2024-09-07T12:45:33.000Z (9 months ago)
- Last Synced: 2024-09-07T14:04:42.950Z (9 months ago)
- Topics: deep-convolutional-networks, deep-learning, inceptionv4, resnet-50
- Language: Jupyter Notebook
- Homepage:
- Size: 12.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Bone age Prediction
## Deep CNN Approaches for predicting bone age from hand X-ray radiographs
Deep ConvolutionalNeural Networks (CNNs) have proven to be a powerful tool
for image classification, image regression, machine vision, and
feature extraction tasks. They have been applied successfully to a
variety of medical imaging tasks, including bone age prediction.
This paper explains how we built deep convolutional neural
networks to predict bone age in months using hand X-ray image
data as input. In order to extract functional results, we used
Inception V4, which is a deep convolutional neural network
(CNN) architecture for image classification and regression tasks.
It was introduced in 2014 by Google researchers and published
in 2016. Another approach that is used is ResNet-50, a deep
convolutional neural network (CNN) architecture for image
classification and machine vision tasks. It was developed by
Microsoft researchers and published in 2015. Although both
of these approaches have different structures and architectures,
they both produce reasonable results.