GinkgoSense-Net detects fruit at 95% under field clutter.

Lab-trained vision models fail on occlusion and shadow; GinkgoSense-Net’s value is robustness to field interference, not benchmark accuracy.

Reliable field detection is the bottleneck for autonomous harvest robots; accurate lab benchmarks don’t transfer.

Sources: Nature