feat: implement comprehensive land cover classification pipeline with model benchmarking and experiment logging

2026-07-17 18:54:25 +07:00
parent a258db54cd
commit abab846884
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+🚀 V4: TÍCH HỢP RADAR SENTINEL-1 (32-CHANNELS FUSION)
+============================================================
+Clean FUSION data: (252, 32, 16, 16), 7 classes, [31, 38, 32, 49, 23, 75, 4]
+
+============================================================
+32-CHANNELS FUSION CNN
+============================================================
+  Ep 1 Fusion-Acc=0.1961 🌟
+  Ep 3 Fusion-Acc=0.2745 🌟
+  Ep 4 Fusion-Acc=0.4706 🌟
+  Ep 5 Fusion-Acc=0.5490 🌟
+  Ep 6 Fusion-Acc=0.7059 🌟
+  Ep 7 Fusion-Acc=0.7451 🌟
+  Ep 8 Fusion-Acc=0.8431 🌟
+  Ep 15 Fusion-Acc=0.8627 🌟
+
+✅ CNN Fusion best: 0.8627
+
+============================================================
+HYBRID FUSION: CNN embed + S1/S2 Rich features + XGBoost
+============================================================
+Extracted 2182 fusion features per sample
+  Final Feature Vector: (252, 2694)
+  ✅ Hybrid Fusion Acc: 0.8627
+    Fold 1: 0.9412
+    Fold 2: 0.9020
+    Fold 3: 0.9200
+    Fold 4: 0.8800
+    Fold 5: 0.9000
+  ✅ CV Mean: 0.9086 ± 0.0206
+
+============================================================
+📊 FINAL RESULTS V4 (WITH RADAR)
+============================================================
+  ✅ Hybrid Fusion CV: 0.9086
+  📈 CNN Fusion (32ch): 0.8627
+  📈 Hybrid Fusion (CNN+XGB): 0.8627
+
+🏆 BEST: 0.9086