Temporal speckle enables probabilistic weights for uncertainty-aware photonic AI
Pernice W +14 more
europepmc +1 more source
Research on deep learning architecture optimization method for intelligent scheduling of structural space. [PDF]
Sci RepYing W, Hui L.
europepmc +1 more source
Review and optimization of image classification models for edge AI applications. [PDF]
Nano ConvergKim S, Cho H, Kim T, Lee H, An S, Ryu S.
europepmc +1 more source
Machine Learning, Deep Learning, and IoT for Waste Classification and Intelligent Waste Management: A PRISMA-Based Systematic Review. [PDF]
Sensors (Basel)Khan MR +6 more
europepmc +1 more source
From Signal Stacking to Dynamic Coupling: A Critical Review of Wearable EEG-EMG Fusion Brain-Computer Interfaces for Stroke Rehabilitation. [PDF]
Micromachines (Basel)Dai M, Jiao M, Wang Y.
europepmc +1 more source
SurgeNAS: A Comprehensive Surgery on Hardware-Aware Differentiable Neural Architecture Search
IEEE Transactions on Computers, 2023 This work is partially supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 2 (MOE2019-T2-1-071) and Tier 1 (MOE2019-T1-001-072), and partially supported by Nanyang Technological University, Singapore, under its NAP (M4082282) and SUG (M4082087).
Weichen Liu, Xiangzhong Luo, Di Liu
exaly +5 more sources
Designing Efficient DNNs via Hardware-Aware Neural Architecture Search and Beyond
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022 Hardware systems integrated with deep neural networks (DNNs) are deemed to pave the way for future artificial intelligence (AI). However, manually designing efficient DNNs involves non-trivial computation resources since significant trial-and-errors are required to finalize the network configuration.
Weichen Liu, Di Liu, Xiangzhong Luo
exaly +5 more sources
A Hardware-Aware Neural Architecture Search Algorithm Targeting Low-End Microcontrollers
2023 18th Conference on Ph.D Research in Microelectronics and Electronics (PRIME), 2023 Hardware-aware neural architecture search (HW NAS), the process of automating the design of neural architectures taking into consideration hardware constraints, has already outperformed the best human designs on many tasks. However, it is known to be highly demanding in terms of hardware, thus limiting access to non-habitual neural network users ...
Edoardo Ragusa +2 more
exaly +5 more sources