Fig. 10 | Scientific Reports

Fig. 10

From: Global attention and local features using deep perceptron ensemble with vision Transformers for landscape design detection

Fig. 10

Side-by-side Grad-CAM and LIME explanations. The Figure was generated using the Matplotlib library (v3.7.1) in Python (v3.10.12). All experiments were implemented in the Google Colab Pro, Kaggle based environment. The following libraries and packages were employed for experimentation, computation, and visualization: Keras (v2.11.0), TensorFlow (v2.11.0), NumPy (v1.24.3), Pandas (v1.5.3), Matplotlib (v3.7.1), Seaborn (v0.12.2), and Grad-CAM implementations (tf-keras-vis v0.8.6 and keras-vis v0.5.0).

Back to article page