Results 61 to 70 of about 41,575 (296)
Advanced Functional Materials, EarlyView.An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Chengshi guidao jiaotong yanjiu［Objective］Earth chamber pressure is a key parameter for EPB (earth pressure balance) shield construction assessment. Accurate prediction of earth chamber pressure helps construction technicians take timely control measures to ensure subway tunnel ...
WANG Bozhi +8 more
doaj +1 more source
Towards incorporating anamorphic fungi in a natural classification – checklist and notes for 2011 [PDF]
Mycosphere, 2012 A complilation of anamorphic names for both Ascomycota and Basidiomycota is provided which comprises 2895 genera. The genera are listed against a backbone of teleomorphic relationships where known.
Wijayawardene DNN, McKenzie EHC, Hyde KD
doaj +1 more source
Unveiling Hidden DNN Defects with Decision-Based Metamorphic Testing
, 2022 Contemporary DNN testing works are frequently conducted using metamorphic testing (MT). In general, de facto MT frameworks mutate DNN input images using semantics-preserving mutations and determine if DNNs can yield consistent predictions.
Yuan, Yuanyuan, Pang, Qi, Wang, Shuai
core +1 more source
Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
MehrasaModanlou/DNN-for-Software-Fault-Prediction: Initial Release
<h2>What's Changed</h2> <ul> <li>Release the first version of the SFP-DNN.ipynb by @MehrasaModanlou in https://github.com/MehrasaModanlou/DNN-for-Software-Fault-Prediction/pull/1</li> </ul> <h2>New Contributors ...
MehrasaModanlou
core +2 more sources
Two hidden layer DNN structure.
, 2021 Two hidden layer DNN structure.
Joan Lu (10661363) +1 more
core +1 more source
Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Advanced Materials, EarlyView.Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
Faster Convergence & Generalization in DNNs
CoRR, 2018 9 pages, 6 ...
Gaurav Singh 0001, John Shawe-Taylor
openaire +2 more sources
Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization
Advanced Materials Technologies, EarlyView.An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue +8 more
wiley +1 more source