Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring

3 July 2020

Papers citing "Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring"

5 / 5 papers shown

Title
An investigation of challenges encountered when specifying training data and runtime monitors for safety critical ML applications Hans-Martin Heyn E. Knauss Iswarya Malleswaran Shruthi Dinakaran 59 4 0 31 Jan 2023
MLDemon: Deployment Monitoring for Machine Learning Systems Antonio A. Ginart Martin Jinye Zhang James Zou 135 20 0 28 Apr 2021
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends Q. Rahman Peter Corke Feras Dayoub OOD 135 55 0 05 Jan 2021
The training accuracy of two-layer neural networks: its estimation and understanding using random datasets Shuyue Guan Murray H. Loew 17 0 0 26 Oct 2020
flexgrid2vec: Learning Efficient Visual Representations Vectors Ali Hamdi D. Kim Flora D. Salim SSL GNN 88 7 0 30 Jul 2020