( en | de | ru )

 

Disambiguation

From post

копироватьудалитьдобавить публикацию в буфер
On the performance of data-driven approaches for energy efficiency on WiFi and LoRa-based sensors: an experimental study.

, , , , и . IWCMC, стр. 883-888. IEEE, (2022)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

Azar Djalali

Azar Ahanchi

Kamal Azar

Azar Nithammer

Azar Shahidizenouz

 

Другие публикации лиц с тем же именем

Lightweight Feature-based Priority Sampling for Industrial IoT Multivariate Time Series., , , и . AICCSA, стр. 1-8. IEEE, (2023)Robust IoT time series classification with data compression and deep learning., , , и . Neurocomputing, (2020)Using DenseNet for IoT multivariate time series classification., , и . ISCC, стр. 1-6. IEEE, (2020)Deep recurrent neural network-based autoencoder for photoplethysmogram artifacts filtering., , , и . Comput. Electr. Eng., (2021)XorshiftH128+: A hybrid random number generator for lightweight IoT., , , , , , и . AIBThings, стр. 1-5. IEEE, (2023)An Efficient and Robust MIoT Communication Solution using a Deep Learning Approach., , , , и . IWCMC, стр. 366-371. IEEE, (2022)A Review of Research on Industrial Time Series Classification for Machinery based on Deep Learning., , , , и . MENACOMM, стр. 89-94. IEEE, (2022)A deep learning scheme for efficient multimedia IoT data compression., , , , и . Ad Hoc Networks, (2023)Efficient Lossy Compression for IoT Using SZ and Reconstruction with 1D U-Net., , , и . Mob. Networks Appl., 27 (3): 984-996 (2022)An energy efficient IoT data compression approach for edge machine learning., , , и . Future Gener. Comput. Syst., (2019)