πΎ MozieFinder
MozieFinder is a lightweight convolutional neural network (CNN) model built from scratch using TensorFlow, designed to classify images as either cats or dogs.
- π¦ Model Type: Custom CNN (ResNet-inspired)
- πΆπ± Task: Binary Image Classification (Cat vs. Dog)
- π§ Trainable Parameters: ~1.2 million
- πΌοΈ Input Resolution: 224x224
- ποΈ Training Data: ~20,000 labeled cat and dog images
- π― Validation Accuracy: ~92%
MozieFinder was trained from scratch β no pre-trained weights were used β as a demonstration of how to build a robust image classification model end-to-end.
β οΈ Disclaimer: This model card was written by the model creator. It has not been officially reviewed by TensorFlow or affiliated teams.
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