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Giraffe. 1. 0.8. Accuracy. NB. 0.6. CENT. LOOPS. GROUND. 0.4. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. # Training Instances (per class). cheetah. 1. 0.8. Accuracy. 0.6. 0.4. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. # Training Instances (per class). airplane. 1. 0.8. Accuracy.

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  1. Giraffe 1 0.8 Accuracy NB 0.6 CENT LOOPS GROUND 0.4 1 2 3 4 5 6 7 8 9 10 # Training Instances (per class)

  2. cheetah 1 0.8 Accuracy 0.6 0.4 1 2 3 4 5 6 7 8 9 10 # Training Instances (per class)

  3. airplane 1 0.8 Accuracy 0.6 0.4 1 2 3 4 5 6 7 8 9 10 # Training Instances (per class)

  4. Lamp thinfat 1 0.8 Accuracy 0.6 0.4 1 2 3 4 5 6 7 8 9 10 # Training Instances (per class)

  5. Lamp trisq 1 0.8 Accuracy 0.6 0.4 1 2 3 4 5 6 7 8 9 10 # Training Instances (per class)

  6. Overlap - Caltech 1 Centroid LOOPS 0.9 0.8 Overlap Score 0.7 0.6 0.5 Airplane Bass Buddha Rooster

  7. Overlap - Mammals 1 0.9 0.8 Overlap Score 0.7 0.6 0.5 Llama Rhino Gir. Bison Deer Ele.

  8. 0.8 Centroid Landmark 0.7 LOOPS 0.6 Landmark Success 0.5 0.4 0.3 Airplane Bass Buddha Rooster

  9. 0.8 0.7 0.6 Landmark Success 0.5 0.4 0.3 Llama Rhino Gir. Bison Deer Ele.

  10. BASE TARGET Cost(311) = 0.397 Cost(152) = 1.223

  11. Simple Training Outlines Corresponded Outlines LOOPS Model Localized Test Outlines Descriptive Classification Up Down +1 std UP -1 std Mean +1 std DOWN -1 std Shape Model (b) Section 4.1 Discrete Inference (c) Section 5 Correspondence (a) Section 3 Shape Classification (d) Section 6.2 Boosted Detectors (b) Section 4.2 Refinement (c) Section 5

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