Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial …
This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for …
B Denby, B Lucia - Proceedings of the Twenty-Fifth International …, 2020 - dl.acm.org
Advances in nanosatellite technology and a declining cost of access to space have fostered an emergence of large constellations of sensor-equipped satellites in low-Earth orbit. Many …
M Xu, M Zhu, Y Liu, FX Lin, X Liu - Proceedings of the 24th annual …, 2018 - dl.acm.org
We present DeepCache, a principled cache design for deep learning inference in continuous mobile vision. DeepCache benefits model execution efficiency by exploiting …
Adaptive optimization methods for deep learning adjust the inference task to the current circumstances at runtime to improve the resource footprint while maintaining the model's …
The increased resolution of real-world videos presents a dilemma between efficiency and accuracy for deep Video Quality Assessment (VQA). On the one hand, keeping the original …
Machine learning (ML) models are widely used in many important domains. For efficiently processing these computational-and memory-intensive applications, tensors of these …
Large deep neural network (DNN) models pose the key challenge to energy efficiency due to the significantly higher energy consumption of off-chip DRAM accesses than arithmetic or …
Wireless sensor networks (WSNs) have various applications which include zone surveillance, environmental monitoring, event tracking where the operation mode is long …