Hugging Face's logo

PogusTheWhisper
/
SurgiCare

Image Classification
Keras
vision
Model card Files
xet
Community
PogusTheWhisper commited on
Commit
cc3b02a
·
verified ·
1 Parent(s): 464bccf

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +7 -7
README.md CHANGED
@@ -27,17 +27,17 @@ SurgiCare is an AI system designed to support post-surgery patient recovery. In
27
  ### EfficientnetV2 B3
28
  * Accuracy: 0.6884
29
 
30
- <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/wound_classify_train/EfficientNetV2B3-standard.png?raw=true" width="800">
31
 
32
  ### MobileNetV3Large
33
  * Accuracy: 0.6164
34
 
35
- <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/wound_classify_train/MobileNetV3Large-standard.png?raw=true" width="800">
36
 
37
  ### MobileNetV3Small
38
  * Accuracy: 0.6199
39
 
40
- <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/wound_classify_train/MobileNetV3Small-standard.png?raw=true" width="800">
41
 
42
  ---
43
 
@@ -46,22 +46,22 @@ SurgiCare is an AI system designed to support post-surgery patient recovery. In
46
  * Accuracy: 0.9127
47
  * Training Details: I used EfficientNet-B3 to train for 50 epochs, monitoring the validation loss.
48
 
49
- <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/wound_classify_train/SurgiCare-V1-large-turbo.png?raw=true" width="800">
50
 
51
  ### Efficientnet B3
52
  * Accuracy: 0.9062
53
  * Training Details: I used EfficientNet-B3 to train for 25 epochs, monitoring the validation loss.
54
 
55
- <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/wound_classify_train/SurgiCare-V1-large.png?raw=true" width="800">
56
 
57
  ### MobileNetV3Large
58
  * Accuracy: 0.7969
59
  * Training Details: I used MobileNetV3Large to train for 50 epochs, monitoring the validation loss.
60
 
61
- <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/wound_classify_train/SurgiCare-V1-medium.png?raw=true" width="800">
62
 
63
  ### MobileNetV3Small
64
  * Accuracy: 0.7812
65
  * Training Details: I used MobileNetV3Small to train for 50 epochs, monitoring the validation loss.
66
 
67
- <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/wound_classify_train/SurgiCare-V1-small.png?raw=true" width="800">
 
27
  ### EfficientnetV2 B3
28
  * Accuracy: 0.6884
29
 
30
+ <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/EfficientNetV2B3-standard.png?raw=true" width="800">
31
 
32
  ### MobileNetV3Large
33
  * Accuracy: 0.6164
34
 
35
+ <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/MobileNetV3Large-standard.png?raw=true" width="800">
36
 
37
  ### MobileNetV3Small
38
  * Accuracy: 0.6199
39
 
40
+ <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/MobileNetV3Small-standard.png?raw=true" width="800">
41
 
42
  ---
43
 
 
46
  * Accuracy: 0.9127
47
  * Training Details: I used EfficientNet-B3 to train for 50 epochs, monitoring the validation loss.
48
 
49
+ <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-large-turbo.png?raw=true" width="800">
50
 
51
  ### Efficientnet B3
52
  * Accuracy: 0.9062
53
  * Training Details: I used EfficientNet-B3 to train for 25 epochs, monitoring the validation loss.
54
 
55
+ <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-large.png?raw=true" width="800">
56
 
57
  ### MobileNetV3Large
58
  * Accuracy: 0.7969
59
  * Training Details: I used MobileNetV3Large to train for 50 epochs, monitoring the validation loss.
60
 
61
+ <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-medium.png?raw=true" width="800">
62
 
63
  ### MobileNetV3Small
64
  * Accuracy: 0.7812
65
  * Training Details: I used MobileNetV3Small to train for 50 epochs, monitoring the validation loss.
66
 
67
+ <img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-small.png?raw=true" width="800">