Add of results from 26 attributes

NoiseDectection-metrics/RESULTS.md

@@ -128,4 +128,27 @@ Use of different way to train data:
 - ipca_diff
 - svd_reconstruct
 - highest_sv_std_filters (use of different filters on images and SVD computed on it)
-- lowest_sv_std_filters (use of different filters on images and SVD computed on it)
+- lowest_sv_std_filters (use of different filters on images and SVD computed on it)
+
+
+# NoiseDetection-26-attributes
+
+## Description
+ 
+All results obtained from [NoiseDetection-26-attributes](https://github.com/prise-3d/Thesis-NoiseDetection-26-attributes.git) project in order to classify noisy or not noisy synthesis images obtained from monte carlo rendering process.
+
+## Results
+
+### 1.FirstResults
+
+#### Description
+
+Study of statistics features extracted from filters applied on synthesis images in order to detect noise.
+
+#### Parameters
+- Kind of normalization (3 differents way)
+- Number of zones taken ramdomly in training set from the 16 available of an image
+
+#### Pool of features
+
+- filters_statistics (statistics obtained from applied fitlers)

NoiseDetection-26-attributes/1.FirstResults/models_comparisons_all.csv

@@ -0,0 +1,46 @@
+model_name, vector_size, start, end, nb_zones, metric, mode, tran_size, val_size, test_size, train_pct_size, val_pct_size, test_pct_size, train_acc, val_acc, test_acc, all_acc, F1_train, recall_train, roc_auc_train, F1_val, recall_val, roc_auc_val, F1_test, recall_test, roc_auc_test, F1_all, recall_all, roc_auc_all
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NoiseDetection-26-attributes/1.FirstResults/models_comparisons_split.csv

@@ -0,0 +1,46 @@
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