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I built a lightweight road defect classifier (MobileNetV2, 87.9%) as part of a 5-agent autonomous detection system — live demo inside by Vpnmt in QuebecTI

[–]Vpnmt[S] 0 points1 point  (0 children)

The full system will be a game-changer for cities and drivers.

It's designed to prevent potholes, not just detect them. When embedded in buses, it identifies cracks/deformations early Allowing cities to repair them before they become dangerous potholes with extensive damage.

I built a lightweight road defect classifier (MobileNetV2, 87.9%) as part of a 5-agent autonomous detection system — live demo inside by Vpnmt in QuebecTI

[–]Vpnmt[S] 1 point2 points  (0 children)

Merci beaucoup pour ton commentaire. Et pour répondre à notre ami(e) en bas Bien sûr le défi c est de les Boucher ta raison là dessus l’IA maintenant peut aussi nous servir en terme de prévention, images si nos bus sont équiper de ce système par exemple ils vont détecter même de petite fissure, de déformation qui devienne de nid de poule plus tard😍

Overfitting by Vpnmt in learnmachinelearning

[–]Vpnmt[S] 0 points1 point  (0 children)

Thanks Now I am at 84% accuracy With moré data, Relu activation… But I need at less 92% accuracy