Documentos de Jiang S. | REDI

Regresar

Mostrando 6 resultados de: 6

Subtipo de publicación

Publisher

ACS Sustainable Chemistry and Engineering(1)

AIChE Journal(1)

Chemical Science(1)

Área temáticas

Física aplicada(3)

Métodos informáticos especiales(3)

Ciencias de la computación(2)

Química física(2)

Electricidad y electrónica(1)

Área de conocimiento

Aprendizaje automático(5)

Ciencia de materiales(2)

Ciencias de la computación(2)

Fibra óptica(1)

Año de Publicación

Origen

Palabras Claves

Machine learning(3)

classification(2)

plastic waste(2)

Convolutional neural nets in chemical engineering: Foundations, computations, and applications

Abstract: In this article, we review the mathematical foundations of convolutional neural nets (CNNs) with the

Palabras claves:

Chemical Engineering, convolutional neural networks, grid data

Jiang S., Víctor M. Zavala

Accurate Characterization of Mixed Plastic Waste Using Machine Learning and Fast Infrared Spectroscopy

Abstract: We present a combination of convolutional neural network (CNN) framework and fast MIR (mid-infrared

Palabras claves:

classification, IR spectra, Machine learning, plastic waste, real-time

Bar-Ziv E., Friis S., Høgstedt L., Jiang S., Long F., Víctor M. Zavala, Zinchik S.

Fast pbkp_redictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks

Abstract: The rates of liquid-phase, acid-catalyzed reactions relevant to the upgrading of biomass into high-v

Palabras claves:

Chew A.K., Jiang S., Van Lehn R.C., Víctor M. Zavala, Zhang W.

Using ATR-FTIR spectra and convolutional neural networks for characterizing mixed plastic waste

Abstract: We present a convolutional neural network (CNN) framework for classifying different types of plastic

Palabras claves:

classification, IR spectra, Machine learning, plastic waste, real-time

Bar-Ziv E., Jiang S., Kamran M., McDonald A.G., Paheding S., Víctor M. Zavala, Xu Z., Zinchik S.

Using machine learning and liquid crystal droplets to identify and quantify endotoxins from different bacterial species

Abstract: Detection and quantification of bacterial endotoxins is important in a range of health-related conte

Palabras claves:

Abbott N.L., Jiang S., Noh J., Park C., Smith A.D., Víctor M. Zavala

Sensing Gas Mixtures by Analyzing the Spatiotemporal Optical Responses of Liquid Crystals Using 3D Convolutional Neural Networks

Abstract: We report how analysis of the spatial and temporal optical responses of liquid crystal (LC) films to

Palabras claves:

Color Features, gas sensor, Liquid crystals, Machine learning, Spatiotemporal patterns

Abbott N.L., Bao N., Jiang S., Mavrikakis M., Schauer J.J., Smith A.D., Van Lehn R.C., Víctor M. Zavala