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Standard Analytical Methods, Sensory Evaluation, NIRS and Electronic Tongue for Sensing Taste Attributes of Different Melon Varieties.

, , , , , , , , and . Sensors, 19 (22): 5010 (2019)

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Chaining Bounds for Empirical Risk Minimization., , and . CoRR, (2016)Neural Architecture Search for Automotive Grid Fusion Networks Under Embedded Hardware Constraints., and . ICMLA, page 79-86. IEEE, (2020)Sensor Fusion Neural Networks for Gesture Recognition on Low-power Edge Devices., , , and . ICAART (2), page 141-150. SCITEPRESS, (2021)Adaptively Partitioning Max-Affine Estimators for Convex Regression.. AISTATS, volume 151 of Proceedings of Machine Learning Research, page 860-874. PMLR, (2022)Standard Analytical Methods, Sensory Evaluation, NIRS and Electronic Tongue for Sensing Taste Attributes of Different Melon Varieties., , , , , , , , and . Sensors, 19 (22): 5010 (2019)Near-optimal max-affine estimators for convex regression., , and . AISTATS, volume 38 of JMLR Workshop and Conference Proceedings, JMLR.org, (2015)Automated Defect Inspection in Reverse Engineering of Integrated Circuits., , , , and . WACV, page 1809-1818. IEEE, (2022)Machine Learning for Grid-Based Sensor Fusion in Automotive Applications (Maschinelles Lernen für die grid-basierte Sensordatenfusion in automobilen Anwendungen). Technical University of Munich, Germany, (2022)Building upon Modularity in Artificial Neural Networks., , and . ERCIM News, (2019)Deep Grid Fusion of Feature-Level Sensor Data with Convolutional Neural Networks., and . ICCVE, page 1-6. IEEE, (2019)