Main Reference PaperResInNet: A Novel Deep Neural Network with Feature Re-use for Internet of Things, IEEE Internet of Things Journal, 2018 [Java]
  • A deep learning framework considering feature re-use, namely Reservoir In Network (ResInNet). It is extended and improved from deep belief echo-state network (DBEN). In this structure, the reservoir plays two notable roles, namely feature re-use and nonlinear approximation. On the one hand, behaves as a bridge between any two restricted Boltzmann machines in the feature learning part of ResInNet, performing a feature abstraction once again. Such reservoir-based feature translation provides excellent starting points for the following nonlinear regression. On the other hand, as a nonlinear approximation, trained by a simple linear regression using the learned features.

+ Description
  • A deep learning framework considering feature re-use, namely Reservoir In Network (ResInNet). It is extended and improved from deep belief echo-state network (DBEN). In this structure, the reservoir plays two notable roles, namely feature re-use and nonlinear approximation. On the one hand, behaves as a bridge between any two restricted Boltzmann machines in the feature learning part of ResInNet, performing a feature abstraction once again. Such reservoir-based feature translation provides excellent starting points for the following nonlinear regression. On the other hand, as a nonlinear approximation, trained by a simple linear regression using the learned features.

  • To improve the accuracy in the network

  • To improve the overall performance in the network

+ Aim & Objectives
  • To improve the accuracy in the network

  • To improve the overall performance in the network

  • A technique is contributed to further improve the performance of the overall network.

+ Contribution
  • A technique is contributed to further improve the performance of the overall network.

  • Operating System : Ubuntu 12.04 LTS 64bit

  • Simulator: Cooja, Instant Contiki-3.0 and Vmware Player 12.5.6

  • Language: C

+ Software Tools & Technologies
  • Operating System : Ubuntu 12.04 LTS 64bit

  • Simulator: Cooja, Instant Contiki-3.0 and Vmware Player 12.5.6

  • Language: C

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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