CNN Model for Breast Cancer Detection
Budget: $350 – $550 USD
I'm seeking a skilled professional to develop a Convolutional Neural Network (CNN) for classifying breast cancer images. The project involves using CBIS-DDSM, MIAS, and INbreast datasets to train the model and evaluating its performance based on specific metrics.
Key Responsibilities:
- Build a CNN model for breast cancer detection.
- Use normalization, data augmentation, and resizing as preprocessing steps.
- Implement the model using VGG16 and ResNet50 architectures.
- Split the data 80% for training and 20% for testing.
Performance Goals:
- Achieve an accuracy of up to 95%.
- Achieve a recall/sensitivity of up to 95%.
- Achieve a specificity of up to 95%.
- Evaluate precision and F1 Score.
Technical Requirements:
- Implement the project using Python with GPU Tensorflow on a native-Windows local environment lab.
- Familiarity with Tensorflow installation on Windows is required.
Ideal Skills:
- Proficiency in Python and Tensorflow.
- Experience with CNN model development.
- Familiarity with breast cancer datasets and related image classification tasks.
- Ability to achieve high performance metrics.
Key Responsibilities:
- Build a CNN model for breast cancer detection.
- Use normalization, data augmentation, and resizing as preprocessing steps.
- Implement the model using VGG16 and ResNet50 architectures.
- Split the data 80% for training and 20% for testing.
Performance Goals:
- Achieve an accuracy of up to 95%.
- Achieve a recall/sensitivity of up to 95%.
- Achieve a specificity of up to 95%.
- Evaluate precision and F1 Score.
Technical Requirements:
- Implement the project using Python with GPU Tensorflow on a native-Windows local environment lab.
- Familiarity with Tensorflow installation on Windows is required.
Ideal Skills:
- Proficiency in Python and Tensorflow.
- Experience with CNN model development.
- Familiarity with breast cancer datasets and related image classification tasks.
- Ability to achieve high performance metrics.