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  - image-classification
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  ---
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  # SurgiCare_V1_best
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- I used EfficientNet-B3 to train for 25 epochs, monitoring the validation loss. /
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- Accuracy: 0.9062 Approximately 11 seconds per image. /
 
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  ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-best.png)
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  # SurgiCare_V1_fast
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- I used MobileNetV3Large to train for 50 epochs, monitoring the validation loss. /
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- Accuracy: 0.7969 Approximately 5 seconds per image. /
 
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  ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-fast.png)
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  # SurgiCare_V1_mini
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- I used MobileNetV3Small to train for 50 epochs, monitoring the validation loss. /
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- Accuracy: 0.7812 Approximately 4 seconds per image. /
 
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  ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-mini.png)
 
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  - image-classification
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  ---
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+ [Github Repo](https://github.com/PogusTheWhisper/SurgiCare.git)
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+
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  # SurgiCare_V1_best
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+ I used EfficientNet-B3 to train for 25 epochs, monitoring the validation loss.
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+ Accuracy: 0.9062 Approximately 11 seconds per image.
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+
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  ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-best.png)
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  # SurgiCare_V1_fast
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+ I used MobileNetV3Large to train for 50 epochs, monitoring the validation loss.
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+ Accuracy: 0.7969 Approximately 5 seconds per image.
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+
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  ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-fast.png)
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  # SurgiCare_V1_mini
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+ I used MobileNetV3Small to train for 50 epochs, monitoring the validation loss.
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+ Accuracy: 0.7812 Approximately 4 seconds per image.
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+
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  ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-mini.png)