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"A digital shadow approach for enhancing process monitoring in wire arc" by Haochen Mu, Fengyang He et al.

With the development of Industry 4.0 and smart manufacturing, improving production automation, intelligence, and digitalization has become a research trend in the Wire Arc Additive Manufacturing (WAAM) field. This study introduces a digital shadow that aims to improve the adaptiveness and dimensionality of monitoring systems in WAAM. Three sensors are used in the digital shadow: a welding electric signal sensor, a camera, and a laser profilometer to collect welding current and voltage data, imag...
Wire Arc Additive Manufacturing Multi Layer Perceptron Variational Autoencoder Defect Detection Digital Shadow Image Processing
Source: uow.edu.au

IMining's AI Subsidiary, AiMining Technologies, Has Appointed Daniel Campbell to Its Scientific Research Board to Propel Artificial Intelligence Innovation

IMining Technologies Inc. , proudly announces the appointment of Daniel Campbell as an Advisor to the Scientific Research Board of its subsidiary, AiMining Technologies. As a leading member of the...
United States British Columbia United Kingdom Saleem Moosa Khurram Shroff Daniel Campbell

Generative AI Market Size Will Grow at a CAGR of 32% by 2023: Unveiling Growth, Trends, and Industry Implications | Valuates Reports

BANGALORE, India, Oct. 24, 2023 /PRNewswire/ -- The Global generative AI market size was valued at USD 8.2 Billion in 2021 and is projected to reach USD 126.5 Billion by 2031, growing at a CAGR of 32% from 2022 to 2031. Major Factors: Generative AI has become more well-known because of its revolutionary effects on a number of...
United States Service Aiaas Market Artificial Intelligence Software System Ai Inc Amazon Web Services Inc Microsoft Corporation

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"Black-Box Audio Adversarial Example Generation Using Variational Autoe" by Wei Zong, Yang Wai Chow et al.

Automatic speech recognition (ASR) applications are ubiquitous these days. A variety of commercial products utilize powerful ASR capabilities to transcribe user speech. However, as with other deep learning models, the techniques underlying ASR models suffer from adversarial example (AE) attacks. Audio AEs resemble non-suspicious audio to the casual listener, but will be incorrectly transcribed by an ASR system. Existing black-box AE techniques require excessive requests sent to a targeted system...
Adversarial Example Automatic Speech Recognition Deep Learning Machine Learning Variational Autoencoder
Source: uow.edu.au

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