Feature optimization-guided high-precision and real-time metal surface defect detection network.

Existing computer vision-based surface defect detection techniques for metal materials typically encounter issues with defect overlap, significant differences within classes, and similarity between defect samples. These issues compromise feature extraction accuracy and result in missed and false detections. This study proposed a feature optimization-guided high-precision and real-time metal surface defect detection network (FOHR Net) to improve defect feature expressiveness.

Water quality monitoring using abnormal tail-beat frequency of crucian carp.

Fish are rapidly becoming favored as convenient sentinels for behavioral assays of toxic chemical exposure. Tail-beat frequency (TBF) of fish is highly correlated with swimming speed, which has been used to detect toxicants. Here we examined the effect on TBF of exposure to two chemicals, and evaluated the ability of this novel behavioral parameter to accurately monitor water quality.