MNIST-NET10: A heterogeneous deep networks fusion based on the degree of certainty to reach 0.1 error rate. Ensembles overview and proposal

30 January 2020

Papers citing "MNIST-NET10: A heterogeneous deep networks fusion based on the degree of certainty to reach 0.1 error rate. Ensembles overview and proposal"

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Title
An Expert Ensemble for Detecting Anomalous Scenes, Interactions, and Behaviors in Autonomous Driving Tianchen Ji Neeloy Chakraborty Andre Schreiber Katherine Rose Driggs-Campbell 146 1 0 23 Feb 2025
BMI Prediction from Handwritten English Characters Using a Convolutional Neural Network N. T. Diba N. Akter S. Chowdhury J. E. Giti 43 0 0 04 Sep 2024
Community-Based Hierarchical Positive-Unlabeled (PU) Model Fusion for Chronic Disease Prediction Yang Wu Xurui Li Xuhong Zhang Yangyang Kang Changlong Sun Xiaozhong Liu 24 3 0 06 Sep 2023
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,636 0 03 Jul 2012