saliency maps for inspection

**Saliency Maps** for semiconductor inspection are **visualizations that highlight which pixels in an image are most important for the model's output** — computed by taking the gradient of the model's prediction with respect to the input image, revealing the sensitivity of the classification to each pixel. **Types of Saliency Maps** - **Vanilla Gradient**: $partial y / partial x$ — the raw gradient of the output with respect to input pixels. - **SmoothGrad**: Average gradients over noisy versions of the input for less noisy maps. - **Integrated Gradients**: Accumulate gradients along the path from a baseline to the input. - **Gradient × Input**: Element-wise product of gradient and input for more visually interpretable maps. **Why It Matters** - **Pixel-Level Explanation**: Shows exactly which pixels influenced the classification at the finest granularity. - **Defect Localization**: Saliency often highlights defect regions even without explicit localization training. - **Quality Assurance**: Validates that inspection models respond to physical defect features, not imaging artifacts. **Saliency Maps** are **the pixel-level importance highlighter** — showing which exact pixels drove the model's defect classification decision.