Brain tumor detection and segmentation from MRI images using CNN and Unet models.
The CNN model is used to detect whether a tumor is there or not. After 15 epochs of training, the calculated accuracy is about 99.6%.
The U-net model is used to segment tumors in MRI images of the brain. After 10 epochs of training, the calculated accuracy is about 98%.
These deep neural networks are implemented with Keras functional API. Use the trained models to detect and segment tumors on brain MRI images. The result is satisfactory.
You can download my U-net trained model from: "https://drive.google.com/drive/folders/1qt7l3HOGIwOguWsMKc5fuwG2NGiGOucf?usp=sharing" and CNN trained model from: "https://drive.google.com/drive/folders/1fXFzMwNG6HrbNp6-GASAgeybeSB3JWCd?usp=sharing".
To access the codes, refer to my GitHub.
Github: https://github.com/AryaKoureshi/Brain-tumor-detection
Website: https://aryakoureshi.github.io/project/BT_detection
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The CNN model is used to detect whether a tumor is there or not. After 15 epochs of training, the calculated accuracy is about 99.6%.
The U-net model is used to segment tumors in MRI images of the brain. After 10 epochs of training, the calculated accuracy is about 98%.
These deep neural networks are implemented with Keras functional API. Use the trained models to detect and segment tumors on brain MRI images. The result is satisfactory.
You can download my U-net trained model from: "https://drive.google.com/drive/folders/1qt7l3HOGIwOguWsMKc5fuwG2NGiGOucf?usp=sharing" and CNN trained model from: "https://drive.google.com/drive/folders/1fXFzMwNG6HrbNp6-GASAgeybeSB3JWCd?usp=sharing".
To access the codes, refer to my GitHub.
Github: https://github.com/AryaKoureshi/Brain-tumor-detection
Website: https://aryakoureshi.github.io/project/BT_detection
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GitHub
GitHub - AryaKoureshi/Brain-tumor-detection: Implementation of medical image segmentation and deep learning framework with CNN…
Implementation of medical image segmentation and deep learning framework with CNN and U-net - AryaKoureshi/Brain-tumor-detection
❤1
Lane Detection With OpenCV (Part 1)
1. Intro
2. Thresholding
3. Perspective Correction
4. Warping
https://dzone.com/articles/lane-detection-with-opencv
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1. Intro
2. Thresholding
3. Perspective Correction
4. Warping
https://dzone.com/articles/lane-detection-with-opencv
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DZone
Lane Detection With OpenCV (Part 1)
In this article, featuring part 1 of 2, we will see how to detect straight lanes in a road using OpenCV and discuss how to eventually extend it for turns.
https://youtu.be/NMeycZYNpWc
New Video watch now
Heart Disease Prediction using Logistic Regression
How to use classification techniques in ML?
New Video watch now
Heart Disease Prediction using Logistic Regression
How to use classification techniques in ML?
Training Machine Learning Models More Efficiently with Dataset Distillation
http://ai.googleblog.com/2021/12/training-machine-learning-models-more.html
Training Machine Learning Models More Efficiently with Dataset Distillation
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http://ai.googleblog.com/2021/12/training-machine-learning-models-more.html
Training Machine Learning Models More Efficiently with Dataset Distillation
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research.google
Training Machine Learning Models More Efficiently with Dataset Distillation
Posted by Timothy Nguyen1, Research Engineer and Jaehoon Lee, Senior Research Scientist, Google Research For a machine learning (ML) algorithm to b...
🎓 GAN-Supervised Dense Visual Alignment
Github: https://github.com/wpeebles/gangealing
Project: https://www.wpeebles.com/gangealing
Paper: https://arxiv.org/abs/2112.04894v1
Dataset: https://paperswithcode.com/dataset/celeba
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Github: https://github.com/wpeebles/gangealing
Project: https://www.wpeebles.com/gangealing
Paper: https://arxiv.org/abs/2112.04894v1
Dataset: https://paperswithcode.com/dataset/celeba
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GitHub
GitHub - wpeebles/gangealing: Official PyTorch Implementation of "GAN-Supervised Dense Visual Alignment" (CVPR 2022 Oral, Best…
Official PyTorch Implementation of "GAN-Supervised Dense Visual Alignment" (CVPR 2022 Oral, Best Paper Finalist) - wpeebles/gangealing
More than 5000+ amazing 🤩 DataSet!!!
Hope you find it useful!!!
https://paperswithcode.com/datasets
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Hope you find it useful!!!
https://paperswithcode.com/datasets
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huggingface.co
Trending Papers - Hugging Face
Your daily dose of AI research from AK
How to built a data science and machine learning roadmap in 2022?
https://venturebeat.com/2022/01/10/how-to-build-a-data-science-and-machine-learning-roadmap-in-2022/amp/
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https://venturebeat.com/2022/01/10/how-to-build-a-data-science-and-machine-learning-roadmap-in-2022/amp/
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VentureBeat
How to build a data science and machine learning roadmap in 2022
Despite the growing enthusiasm for DSML's core technologies, getting results from its strategies is elusive for enterprises.
Found some good books on Clustering Algorithms:
Book1: Cluster Analysis: Basic Concept
Book2: DATA CLUSTERING Algorithms and Applications
Book3: Algorithms for Clustering Data
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Book1: Cluster Analysis: Basic Concept
Book2: DATA CLUSTERING Algorithms and Applications
Book3: Algorithms for Clustering Data
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YouTube: https://www.youtube.com/c/asifimmanad
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Telegram
Artificial Intelligence
This Channel is to spread knowledge on Artificial Intelligence.❤️
We are here to simplify and understand everything about Artificial Intelligence.🤖
Join us in this mission.❤️
Let’s Grow Together.😍
eduai.web@gmail.com
We are here to simplify and understand everything about Artificial Intelligence.🤖
Join us in this mission.❤️
Let’s Grow Together.😍
eduai.web@gmail.com
Scaling and managing ML models is becoming easier using MLOps with Kubernetes
https://towardsdatascience.com/mlops-with-kubernetes-rabbitmq-and-fastapi-b67d82e35fa4
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https://towardsdatascience.com/mlops-with-kubernetes-rabbitmq-and-fastapi-b67d82e35fa4
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New Video watch now
Math behind Logistic Regression/ Classification technique using Sigmoid function
https://youtu.be/165sOkHniJc
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Math behind Logistic Regression/ Classification technique using Sigmoid function
https://youtu.be/165sOkHniJc
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An introduction to Probabilities and Statistics like no other:
Seeing Theory: https://seeing-theory.brown.edu/
Brown University.
Free.
This interactive website will take you through the concepts you need in machine learning.
#freecourse #probability #statistics
Credit: Twitter (svpino)
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Seeing Theory: https://seeing-theory.brown.edu/
Brown University.
Free.
This interactive website will take you through the concepts you need in machine learning.
#freecourse #probability #statistics
Credit: Twitter (svpino)
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seeing-theory.brown.edu
Seeing Theory
A visual introduction to probability and statistics.
A friendly introduction to machine learning compilers and optimizers
#beginner #datascience #machinelearning
https://huyenchip.com/2021/09/07/a-friendly-introduction-to-machine-learning-compilers-and-optimizers.html
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#beginner #datascience #machinelearning
https://huyenchip.com/2021/09/07/a-friendly-introduction-to-machine-learning-compilers-and-optimizers.html
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Chip Huyen
A friendly introduction to machine learning compilers and optimizers
[Twitter thread, Hacker News discussion]
Separating Birdsong in the Wild for Classification
http://ai.googleblog.com/2022/01/separating-birdsong-in-wild-for.html
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http://ai.googleblog.com/2022/01/separating-birdsong-in-wild-for.html
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research.google
Separating Birdsong in the Wild for Classification
Posted by Tom Denton, Software Engineer and Scott Wisdom, Research Scientist, Google Research Birds are all around us, and just by listening, we ca...
New Video watch now
Confusion Matrix, How to Measure Accuracy in Machine Learning
https://youtu.be/oYMxCvNM4Wk
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Confusion Matrix, How to Measure Accuracy in Machine Learning
https://youtu.be/oYMxCvNM4Wk
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