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Refinado por: assunto: Chemistry remover assunto: Feature Compression remover
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1
The NuMI neutrino beam
The NuMI neutrino beam
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The NuMI neutrino beam

Coelho, João De Abreu Barbosa, 1984-; Escobar, Carlos Ourivio, 1948- Universidade Estadual de Campinas (Unicamp); Universidade Estadual De Campinas

COELHO, João de Abreu Barbosa; ESCOBAR, Carlos Ourivio. The NuMI neutrino beam. Nuclear instruments & methods in physics research. Section A, Accelerators spectrometers detectors and associated equipment. Amsterdam : Elsevier, 2016. Vol. 806 (Jan., 2016), p. 279-306. Disponível em: https://hdl.handle.net/20.500.12733/1666957. Acesso em: 16 nov. 2023.

2016

Acesso online

2
BBNet: A Novel Convolutional Neural Network Structure in Edge-Cloud Collaborative Inference
BBNet: A Novel Convolutional Neural Network Structure in Edge-Cloud Collaborative Inference
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BBNet: A Novel Convolutional Neural Network Structure in Edge-Cloud Collaborative Inference

Zhou, Hongbo ; Zhang, Weiwei ; Wang, Chengwei ; Ma, Xin ; Yu, Haoran

Sensors (Basel, Switzerland), 2021-06, Vol.21 (13), p.4494 [Periódico revisado por pares]

MDPI

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3
An Efficient Compression Method for Lightning Electromagnetic Pulse Signal Based on Convolutional Neural Network and Autoencoder
An Efficient Compression Method for Lightning Electromagnetic Pulse Signal Based on Convolutional Neural Network and Autoencoder
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An Efficient Compression Method for Lightning Electromagnetic Pulse Signal Based on Convolutional Neural Network and Autoencoder

Guo, Jinhua ; Wang, Jiaquan ; Xiao, Fang ; Zhou, Xiao ; Liu, Yongsheng ; Ma, Qiming

Sensors (Basel, Switzerland), 2023-04, Vol.23 (8), p.3908 [Periódico revisado por pares]

Switzerland: MDPI AG

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4
Fast and Accurate Lane Detection via Graph Structure and Disentangled Representation Learning
Fast and Accurate Lane Detection via Graph Structure and Disentangled Representation Learning
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Fast and Accurate Lane Detection via Graph Structure and Disentangled Representation Learning

He, Yulin ; Chen, Wei ; Li, Chen ; Luo, Xin ; Huang, Libo

Sensors (Basel, Switzerland), 2021-07, Vol.21 (14), p.4657 [Periódico revisado por pares]

Basel: MDPI AG

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5
Loop Closure Detection Based on Compressed ConvNet Features in Dynamic Environments
Loop Closure Detection Based on Compressed ConvNet Features in Dynamic Environments
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Loop Closure Detection Based on Compressed ConvNet Features in Dynamic Environments

Jiang, Shuhai ; Zhou, Zhongkai ; Sun, Shangjie

Applied sciences, 2023-12, Vol.14 (1), p.8 [Periódico revisado por pares]

MDPI AG

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6
On the use of a self organising map as feature compressor in the building of calibration models: Application to FTIR-spectrophotometry
On the use of a self organising map as feature compressor in the building of calibration models: Application to FTIR-spectrophotometry
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On the use of a self organising map as feature compressor in the building of calibration models: Application to FTIR-spectrophotometry

Llobet, Eduard ; Anaimi, Mohamed ; Pruñonosa, Alba ; Gras, Eloi

Sensors and actuators. B, Chemical, 2011-11, Vol.158 (1), p.252-258 [Periódico revisado por pares]

Elsevier B.V

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7
Feature selection versus feature compression in the building of calibration models from FTIR-spectrophotometry datasets
Feature selection versus feature compression in the building of calibration models from FTIR-spectrophotometry datasets
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Feature selection versus feature compression in the building of calibration models from FTIR-spectrophotometry datasets

Vergara, Alexander ; Llobet, Eduard

Talanta (Oxford), 2012-01, Vol.88, p.95-103 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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Deste Autor:

  1. Pedro, G
  2. Jacomo, A
  3. Maffei, L
  4. Garcia, W
  5. Garcia, V

Neste Assunto:

  1. Chemistry
  2. Feature Compression
  3. Technology
  4. Feature Compression
  5. Chemistry

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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