Update README.md
Browse files
README.md
CHANGED
@@ -10,4 +10,4 @@ resizing to 256x256 and then converting to grayscale and then applying the Fouri
|
|
10 |
4. Feed into model input
|
11 |
|
12 |
The model will then transform the input transform into a 128-length embedding vector. These vectors are separable and can be used in classification models.
|
13 |
-
The model doesn't enforce a specific classification model, prototypical networks, XGBoost, and other classifiers can be used to classify.
|
|
|
10 |
4. Feed into model input
|
11 |
|
12 |
The model will then transform the input transform into a 128-length embedding vector. These vectors are separable and can be used in classification models.
|
13 |
+
The model doesn't enforce a specific classification model, prototypical networks, XGBoost, and other classifiers can be used to classify. For more detailed instructions refer to [Kaggle](https://www.kaggle.com/models/nhrade/cgi-embedding-detection-module).
|