Identifying the Context Shift between Test Benchmarks and Production Data

3 July 2022

Papers citing "Identifying the Context Shift between Test Benchmarks and Production Data"

9 / 9 papers shown

Title
Towards Reliable Dermatology Evaluation Benchmarks Fabian Gröger Simone Lionetti Philippe Gottfrois Alvaro Gonzalez-Jimenez Matthew Groh Roxana Daneshjou Labelling Consortium Alexander A. Navarini Marc Pouly 31 5 0 13 Sep 2023
Operationalizing Machine Learning: An Interview Study Shreya Shankar Rolando Garcia J. M. Hellerstein Aditya G. Parameswaran 71 51 0 16 Sep 2022
Perspectives on Incorporating Expert Feedback into Model Updates Valerie Chen Umang Bhatt Hoda Heidari Adrian Weller Ameet Talwalkar 30 11 0 13 May 2022
Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set Roxana Daneshjou Kailas Vodrahalli R. Novoa Melissa Jenkins Weixin Liang ... Rachna Sahasrabudhe Johan A. C. Allerup Utako Okata-Karigane James Zou A. Chiou 56 217 0 15 Mar 2022
Evaluating Deep Neural Networks Trained on Clinical Images in Dermatology with the Fitzpatrick 17k Dataset Matthew Groh Caleb Harris L. Soenksen Felix Lau Rachel Han Aerin Kim A. Koochek Omar Badri 112 182 0 20 Apr 2021
DeepFake Detection: Current Challenges and Next Steps Siwei Lyu 55 158 0 11 Mar 2020
Deep Facial Expression Recognition: A Survey Shan Li Weihong Deng 151 1,280 0 23 Apr 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,959 0 20 Apr 2018
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,217 0 01 Sep 2014