On the calibration of sensor arrays for pattern recognition using the minimal number of experiments

By Irene Rodríguez-Luján, Jordi Fonollosa, Alexander Vergara, M. Homer, Ramón Huerta. 2014

193 citations recorded by the source corpus.

Subfields: Bioengineering, Biomedical Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Bioengineering

1. Sanjeev Arora
2. Nadav Cohen

In Biomedical Engineering

1. Elad Hazan
2. Sanjeev Arora
3. Wei Hu
4. Nadav Cohen
5. Lei Zhang
6. David Dapeng Zhang

Citations in the corpus

• A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks (2018, methodology): “The dataset chosen for the ex-periment was UCI Machine Learning Repository’s “Gas Sensor Array Drift at Different Concen-trations” (Vergara et al., 2012; Rodriguez-Lujan et al., 2014).”
• On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization (2018, methodology): “The dataset chosen was UCI Machine Learning Repository’s “Gas Sensor Array Drift at Different Concentrations” (Ver-gara et al., 2012; Rodriguez-Lujan et al., 2014).”
• Domain Adaptation Extreme Learning Machines for Drift Compensation in E-Nose Systems (2015, methodology): “al Data For verification of the proposed DAELM-S and DAELM-T algorithms, the long-term sensor drift big data of three years that was released in UCI Machine Learning Repository [31] by Vergara et al. [26, 30] is exploited and studied in this paper. The sensor drift big dataset was gathered during th”