Semiconductor defect patterns
Classify wafer-map patterns and quantify defect clusters and densities.
Example outputs shown for illustration. Numbers depend on your samples and protocol.
What you get
The measurement, today
Wafer-map signatures (rings, scratches, edge clusters) are read by experienced engineers and rarely classified consistently at scale.
From image to reviewed result
- 1
Calibrate the scale
Set spatial scale from a bar or known dimension. Every downstream number inherits real units.
- 2
Detect & segment
Segmentation models find the objects and regions of interest: grains, particles, pores, fibers, cells.
- 3
Measure
Quantify size, count, area fraction, density, and orientation. The metrics your method already defines.
- 4
Review the overlay
Inspect the result on every field. Adjust thresholds by hand; the change is logged with the output.
- 5
Export & compare
Publication-ready statistics, plus batch comparison across lots, conditions, and time points.
Related applications
Critical dimension (CD) metrology
Line width, space, and via diameter measured from top-down images, with per-feature tables.
Wafer defect map & binning
Detect, locate, size, and bin defects across a wafer into a spatial map.
Photoresist pattern defects
Detect resist pattern collapse, bridging, footing, and scumming after develop.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
