Results 41 to 50 of about 16,838,211 (334)

VEDLIoT: Very Efficient Deep Learning in IoT

, 2022
Kaiser M, Griessl R, Kucza N, et al. VEDLIoT: Very Efficient Deep Learning in IoT. In: Institut of Electrical and Electronics Engineers (IEEE), ed. DATE '22: Proceedings of the 2022 Conference & Exhibition on Design, Automation & Test in Europe ...
Salomonsson, Hans,, Schiavoni, V., Malekzadeh, E.,, McIerhofer, F.,, Knauss, E., Haumann, Carola, Mohammad Qararyah, Fareed,, Casimiro, A., Brunnegård, Oliver,, Krupop, Stefan,, Hagemeyer, Jens, Salomonsson, Hans, Pasin, Marcelo,, Gugala, Karol, Gugala, K., Kaiser, Martin,, Porrmann, M., Pasin, Marcelo, Cecilio, J.,, Heyn, Hans-Martin, Eriksson, Olof, Porrmann, Mario,, Salomonsson, H., Institut of Electrical and Electronics Engineers (IEEE), Brunneg\ue5rd, Oliver, Heyn, Hans-Martin,, Andersson, Stefan, Eriksson, O., Petersen Moura Trancoso, Pedro,, Porrmann, Mario, Vor Dem Berge, Micha, Mika, Kevin ; https://orcid.org/, Ménétrey, Jämes, Brunnegard, O., Menetrey, J.,, Kucza, Nils,, Mika, Kevin, Casimiro, A.C., Tigges, Lennart, Felber, Pascal, Tassemeier, Marco, Ruckert, U., Porrmann, Florian, Bessani, A., Odman, D.,, Malekzadeh, E., Odman, D., Hagemeyer, Jens,, Vor Dem Berge, Micha,, Gugala, K.,, Menetrey, J., Malekzadeh, Elaheh, Qararyah, Fareed, Felber, Pascal,, Porrmann, Florian ; https://orcid.org/, Eriksson, O.,, Andersson, S.,, Kaiser, Martin ; https://orcid.org/, Petersen Moura Trancoso, Pedro, Knauss, Eric, Kucza, Nils, Tigges, L.,, Berge, Micha, Heyn, H., Kucza, N., Kucza, Nils ; https://orcid.org/, Khurshid, A.,, Andersson, S., Zierhoffer, P.,, Zouzoula, S., Zouzoula, Stavroula,, Schiavoni, Valerio, Hagemeyer, J., Kaiser, M., Mika, K.,, Trancoso, Pedro, Krupop, S., Schiavoni, Valerio,, Felber, P., Haumann, C.,, Porrmann, F., Zierhoffer, Piotr, Qararyah, F., Zouzoula, Stavroula, Kaiser, Martin, Weiss, R., Weiss, Roland, Heyn, Hans Martin, Zierhoffer, P., Krupop, Stefan, Tassemeier, M., Tigges, L., vor dem Berge, M., Tassemeier, M.,, Trancoso, P., Weiss, R.,, Bessani, A.,, Ruckert, U.,, Griessl, R.,, Mika, K., Mcierhofer, F., Khurshid, A., Porrmann, F.,, Bessani, Alysson, Cecilio, J., Ödman, Daniel, Khurshid, Anum, Pasin, M., Haumann, C., Griessl, R., Casimiro, A.C.,, Meierhöfer, Franz, Griessl, René, Rückert, Ulrich, Knauss, Eric,, Khurshid, Anum,, Krupop, Stefan., Casimiro, Antonio, Gugula, Karol, Quararyah, Fareed, Cecilio, Jose, Heyn, H.,, Brunnegard, Oliver, Kaiser, M.,, dem Berge, Micha vor, U. Ruckert, R. Griessl, K. Mika, M. Kaiser, K. Gugala, P. Felber, D. Odman, N. Kucza, C. Haumann, O. Eriksson, E. Malekzadeh, M. Pasin, M. Porrmann, F. Porrmann, J. Hagemeyer, O. Brunnegard, S. Zouzoula, S. Krupop, A. Bessani, R. Weiss, J. Cecilio, V. Schiavoni, A. Khurshid, H. Heyn, P. Zierhoffer, F. Mcierhofer, H. Salomonsson, A. Casimiro, F. Qararyah, E. Knauss, M. Tassemeier, M. vor dem Berge, P. Trancoso, S. Andersson, J. Menetrey, L. Tigges   +160 more
core   +1 more source

SOLAR ENERGY FORECASTING WITH DEEP LEARNING TECHNIQUE [PDF]

, 2023
The increasing reliance on renewable energy sources, such as solar power, necessitates accurate forecasting to ensure efficient grid integration and stability.
Kelvin Edem Bassey
core   +1 more source

Hardware acceleration for power efficient deep packet inspection [PDF]

, 2012
The rapid growth of the Internet leads to a massive spread of malicious attacks like viruses and malwares, making the safety of online activity a major concern. The use of Network Intrusion Detection Systems (NIDS) is an effective method to safeguard the
Zhou, Yachao
core   +1 more source

Integrating nanotechnology with deep learning for engineering, healthcare, and environmental solutions: A review [PDF]

EPJ Web of Conferences
Combining nanotechnology and deep learning methods is a leading-edge frontier in engineering solutions, with unparalleled prospects for innovation and growth.
Israni Riaz, Parmar Jaydeep, Chauhan Mehul, Maniya Hina, Singh Brij Pal, Purohit Harsh, Kamdar Jignesh   +6 more
doaj   +1 more source

An Efficient Deep Learning Framework for Intelligent Energy Management in IoT Networks

IEEE Internet of Things Journal, 2021
Green energy management is an economical solution for better energy usage, but the employed literature lacks focusing on the potentials of edge intelligence in controllable Internet of Things (IoT).
Tao Han, Muhammad Khan, Tanveer Hussain, Jaime Lloret, S. Baik   +4 more
semanticscholar   +1 more source

Advanced Deep Learning-Based Computational Offloading for Multilevel Vehicular Edge-Cloud Computing Networks

IEEE Access, 2020
The promise of low latency connectivity and efficient bandwidth utilization has driven the recent shift from vehicular cloud computing (VCC) towards vehicular edge computing (VEC).
Mashael Khayyat, Ibrahim A. Elgendy, Ammar Muthanna, Abdullah S. Alshahrani, Soltan Alharbi, Andrey Koucheryavy   +5 more
doaj   +1 more source

On-line building energy optimization using deep reinforcement learning [PDF]

, 2018
Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the future power systems and to help customers transition from a passive to an ...
Liotta, A., Liotta, Antonio, Gibescu, M., Mocanu, Elena, Decebal Constantin Mocanu, Nguyen, P.H.; id_orcid, Phuong H. Nguyen, Mocanu, D.C., Nguyen, P.H., Slootweg, JG, J. G. Slootweg, Webber, M.E., Michael E. Webber, Madeleine Gibescu, Webber, Michael E., Mocanu, Decebal Constantin, Mocanu, E., Gibescu, Madeleine, Slootweg, J. G., Mocanu, D.C.; id_orcid, Nguyen, Phuong H., Elena Mocanu, Slootweg, J.G., Antonio Liotta   +23 more
core   +1 more source

Deep learning for energy-efficient wireless communications and spectrum management.

, 2020
In the past couple of decades, wireless communication has undergone rapid development. The current fourth generation and upcoming fifth generation wireless technologies promise us an ultra-fast data rate.
Xing, Yuan, 1992-
core   +2 more sources

Overview of Applications and Research Directions of Deep Learning Methods for Wind Power Prediction [PDF]

Jisuanji kexue yu tansuo
As the global demand for renewable energy increases, wind power, as an important part of clean renewable energy, the accurate prediction of its power is crucial for the stable operation of the power system and the efficient use of energy. In recent years,
LIU Tan, LIU Na, LIU Guiping, LIU Kunjie, LIU Min, ZHUANG Xufei, ZHANG Zhonghao
doaj   +1 more source

Energy-efficient deep learning-based intrusion detection system for edge computing: a novel DNN-KDQ model

Journal of Cloud Computing
The proliferation of the Internet of Things (IoT) and edge computing technologies has expanded the attack surface for cybercriminals, emphasizing the need for robust and efficient cybersecurity measures.
Hafiz Gulfam Ahmad Umar, Iqra Yasmeen, Muhammad Aoun, Tehseen Mazhar, Muhammad Amir Khan, Ines Hilali Jaghdam, Habib Hamam   +6 more
semanticscholar   +1 more source