Results 11 to 20 of about 16,838,211 (334)
Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers [PDF]
2025 IEEE Symposium on Computers and Communications (ISCC)In this paper, we present a practical deep learning (DL) approach for energy-efficient traffic classification (TC) on resource-limited microcontrollers, which are widely used in IoT-based smart systems and communication networks.
Adel Chehade +3 more
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Towards Energy Efficient Home Automation: A Deep Learning Approach [PDF]
Sensors, 2020 Home Automation Systems (HAS) attracted much attention during the last decade due to the developments in new wireless technologies, such as Bluetooth 4.0, 5G, WiFi 6, etc.
Murad Khan, Junho Seo, Dongkyun Kim
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Energy-Efficient GPU Clusters Scheduling for Deep Learning [PDF]
CoRR, 2023 Training deep neural networks (DNNs) is a major workload in datacenters today, resulting in a tremendously fast growth of energy consumption. It is important to reduce the energy consumption while completing the DL training jobs early in data centers. In
Dian-Dian Gu +4 more
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Energy-Efficient IoT Sensor Calibration With Deep Reinforcement Learning [PDF]
IEEE Access, 2020 The modern development of ultra-durable and energy-efficient IoT based communication sensors has much application in modern telecommunication and networking sectors.
Akm Ashiquzzaman +3 more
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Energy-Efficient UAV Communications with Interference Management: Deep Learning Framework [PDF]
2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2020 In this paper, an interference-aware energy- efficient scheme for a network of coexisting aerial-terrestrial cellular users is proposed. In particular, each aerial user aims at achieving a trade-off between maximizing energy efficiency and spectral efficiency while minimizing the incurred interference on the terrestrial users along its path. To provide
Jantti, Riku, Ghavimi, Fayezeh
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Applied SciencesWireless sensor networks (WSNs) are widely used in environmental monitoring, industrial automation, and smart cities. The Hybrid Energy-Efficient Distributed (HEED) protocol is a popular clustering algorithm designed to prolong network lifetime by ...
Abdulla Juwaied +1 more
doaj +2 more sources
Energy-Efficient Deep Learning for Cloud Detection Onboard Nanosatellite
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingDeep learning has been increasingly utilized for cloud detection in Earth observation nanosatellites, offering effective solutions to enhance mission performance.
Imane Khalil +4 more
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Dynamic Bit-width Reconfiguration for Energy-Efficient Deep Learning Hardware
Proceedings of the International Symposium on Low Power Electronics and Design, 2018 Deep learning models have reached state of the art performance in many machine learning tasks. Benefits in terms of energy, bandwidth, latency, etc., can be obtained by evaluating these models directly within Internet of Things end nodes, rather than in ...
D. J. Pagliari, E. Macii, M. Poncino
semanticscholar +2 more sources
Energy-Efficient and Improved Image Recognition with Conditional Deep Learning
ACM Journal on Emerging Technologies in Computing Systems, 2017 Deep-learning neural networks have proven to be very successful for a wide range of recognition tasks across modern computing platforms. However, the computational requirements associated with such deep nets can be quite high, and hence their energy-efficient implementation is of great interest.
Priyadarshini Panda +2 more
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Optimizing model pruning for energy-efficient deep learning
Annals of Mathematics and Computer ScienceDeep learning models have become increasingly complex, leading to high energy consumption during training and inference phases. This paper investigates the use of model pruning techniques to significantly reduce the size of deep learning models while ...
Saidjon Kamolov
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