Merge pull request #436 from the-silent-geek/Bone_marrow_cell_classif…

…ication Bone Marrow Cells Classification using Deep Learning
abhisheks008 · Jan 13, 2024 · 7b4f3dd · 7b4f3dd
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diff --git a/Bone Marrow Cells Classification using Deep Learning/README.md b/Bone Marrow Cells Classification using Deep Learning/README.md
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+# <h1 align = "center"> Bone marrow cell classification</h1>
+## Aim of the project: 
+### The project focuses on classification of different types of cells using various Deep Learning Algorithms.
+
+###  Libraries and Frameworks used:
+1. Pandas
+2. Numpy 
+3. Matplotlib
+4. Seaborn
+5. Tensorflow
+6. Keras
+7. sklearn
+
+
+## Deep Learning Algorithms used:
+1. Vgg16
+2. EfficientNetB5
+3. DenseNet
+4. MobileNet
+
+## Accuracy and training time comparison of all the Deep Learning Algorithms
+|                |   Accuracy    |
+|----------------|---------------|
+|     Vgg16      |     90%       |
+| EfficientNetB5 |     92%       |  
+|    DenseNet    |     81%       |     
+|   MobileNet    |     86%       |
+
+# Representation of types of cells
+![EDA](https://github.com/the-silent-geek/DL-Simplified/blob/64d196ea11684a3a2df59b58b912244d9cc8d3fb/Bone%20marrow%20cell%20classification/images/EDA.png)
+
+# Accuracy plots of all models
+
+## Vgg16
+![vgg16](https://github.com/the-silent-geek/DL-Simplified/blob/64d196ea11684a3a2df59b58b912244d9cc8d3fb/Bone%20marrow%20cell%20classification/images/VGG16.png)
+
+## EfficientNetB5
+![EfficientNetB5](https://github.com/the-silent-geek/DL-Simplified/blob/64d196ea11684a3a2df59b58b912244d9cc8d3fb/Bone%20marrow%20cell%20classification/images/efficient%20net%20b5.png)
+
+## DenseNet
+![densenet](https://github.com/the-silent-geek/DL-Simplified/blob/64d196ea11684a3a2df59b58b912244d9cc8d3fb/Bone%20marrow%20cell%20classification/images/DenseNet.png)
+
+## MobileNet
+![mobilenet](https://github.com/the-silent-geek/DL-Simplified/blob/64d196ea11684a3a2df59b58b912244d9cc8d3fb/Bone%20marrow%20cell%20classification/images/mobileNet.png)
+
+# Conclusion
+EfficientNetB5 model performs better comparative to other models used on the above dataset.
diff --git a/Bone Marrow Cells Classification using Deep Learning/dataset/README.md b/Bone Marrow Cells Classification using Deep Learning/dataset/README.md
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+# Dataset
+
+The dataset used in this project is take from the Kaggle website.
+<br>
+<b>Dataset Link:- https://www.kaggle.com/datasets/andrewmvd/bone-marrow-cell-classification/data</b>
+<br>
+
+<br>
+The dataset contains a collection of over 170,000 de-identified, expert-annotated cells from the bone marrow smears of 945 patients stained using the May-Grünwald-Giemsa/Pappenheim stain.
+<br>
diff --git a/Bone Marrow Cells Classification using Deep Learning/images/DenseNet.png b/Bone Marrow Cells Classification using Deep Learning/images/DenseNet.png
diff --git a/Bone Marrow Cells Classification using Deep Learning/images/EDA.png b/Bone Marrow Cells Classification using Deep Learning/images/EDA.png
diff --git a/Bone Marrow Cells Classification using Deep Learning/images/VGG16.png b/Bone Marrow Cells Classification using Deep Learning/images/VGG16.png
diff --git a/Bone Marrow Cells Classification using Deep Learning/images/efficient net b5.png b/Bone Marrow Cells Classification using Deep Learning/images/efficient net b5.png
diff --git a/Bone Marrow Cells Classification using Deep Learning/images/mobileNet.png b/Bone Marrow Cells Classification using Deep Learning/images/mobileNet.png
diff --git a/Bone Marrow Cells Classification using Deep Learning/model/model.ipynb b/Bone Marrow Cells Classification using Deep Learning/model/model.ipynb
diff --git a/Bone Marrow Cells Classification using Deep Learning/requirements.txt b/Bone Marrow Cells Classification using Deep Learning/requirements.txt
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+Pandas
+Numpy 
+Matplotlib
+Seaborn
+Tensorflow
+Keras
+sklearn