most citedProbabilistic Object Classification using CNN ML-MAP layers

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2022

Reducing Overconfidence Predictions for Autonomous Driving Perception

Gledson Melotti, Cristiano Premebida, Jordan J. Bird +2

In state-of-the-art deep learning for object recognition, SoftMax and Sigmoid functions are most commonly employed as the predictor outputs. Such layers often produce overconfident…

cs.LG2020★ 1 cited

Probabilistic Object Classification using CNN ML-MAP layers

G. Melotti, C. Premebida, J. J. Bird +2

Deep networks are currently the state-of-the-art for sensory perception in autonomous driving and robotics. However, deep models often generate overconfident predictions precluding…