https://matteocampagna.com/en/registry/competition/automatic-scoring-target-images Changes to this claim in Matteo Campagna's evidence registry: its status, its year-by-year history, revisions of the page. en-gb https://matteocampagna.com/en/registry/competition/automatic-scoring-target-imagesIn the laboratory, yes; in the field, not yet. Prototypes that read the holes from images work well in clean conditions: the first, with four archers at 10 m indoors, assigns the right score in every sequence tested, and the most accurate, from 2026, locates the holes on a 40 cm face with an error of 1.41 mm and misses the average score per arrow by a median of 1.8 per cent. But the only field test with archers actually shooting, checked against the judges' scores, detects 91 arrows out of 100 and scores 67 of them correctly. The weak points are always the same: arrows that touch or cover another arrow's hole, worn faces, changing light. On torn faces a system trained on smartphone photos drops to around 40 per cent, and even the best one misses about one hole in six, mostly those of tightly grouped arrows, which means the best ends. The two tests with real archers shooting point in opposite directions, and neither was run outdoors at 70 m or over a full round.claim:punteggio-automatico-immagini:revision:2026-06-03:3Wed, 03 Jun 2026 08:00:00 GMT https://matteocampagna.com/en/registry/competition/automatic-scoring-target-imagesclaim:punteggio-automatico-immagini:new_claim:2026-04-20:contestatoMon, 20 Apr 2026 08:00:00 GMT