Results 231 to 240 of about 86,374 (257)

Mixed-signal circuits for embedded machine-learning applications

2015 49th Asilomar Conference on Signals, Systems and Computers, 2015
Machine learning algorithms are attractive solutions for a number of problems in data analytics and sensor signal classification. However, to enable the deployment of such algorithms in embedded hardware, significant progress must be made to reduce the large power dissipation of current GPU and FPGA-based implementations. Our work studies the trade-off
Boris Murmann, Daniel Bankman, Elaina Chai, Daisuke Miyashita, Lita Yang   +4 more
openaire   +1 more source

On Embedding Backdoor in Malware Detectors Using Machine Learning

2019 17th International Conference on Privacy, Security and Trust (PST), 2019
Researching for malware detection using machine learning is becoming active. However, conventional detection techniques do not consider the impact of attacks on machine learning, which has become complicated in recent years. In this research, we focus on data poisoning attack, which is one of the typical attacks on machine learning, and aim to clarify ...
Shoichiro Sasaki, Seira Hidano, Toshihiro Uchibayashi, Takuo Suganuma, Masahiro Hiji, Shinsaku Kiyomoto   +5 more
openaire   +1 more source

Embedded Online Machine Learning

2021 International Conference Engineering and Telecommunication (En&T), 2021
Nikita Yudin, Dmirty Kamzolov, Vadim Sinolits, Pavel Golovkin, Alexey Erchenko   +4 more
openaire   +1 more source

Embedding metric learning into an extreme learning machine for scene recognition

Expert Systems with Applications, 2022
Chen Wang 0058, Guohua Peng, Bernard De Baets   +2 more
openaire   +1 more source

Minimum variance-embedded kernelized extension of extreme learning machine for imbalance learning

Pattern Recognition, 2021
Bhagat Singh Raghuwanshi, Sanyam Shukla
exaly  

An embedded system for remote monitoring and fault diagnosis of photovoltaic arrays using machine learning and the internet of things

Renewable Energy, 2023
A Mellit, Mohamed Benghanem, Soteris A Kalogirou   +2 more
exaly  

Quantum word embedding for machine learning

Physica Scripta
Abstract The accelerated progress in quantum computing has enabled a new form of machine intelligence that runs on quantum hardware, which holds great promise for more powerful computational models in various learning tasks. An emergent application of Quantum Machine Intelligence (QMI) is Quantum Natural Language Processing (QNLP).
openaire   +1 more source

An Efficient FPGA-Based Hardware Accelerator for Convex Optimization-Based SVM Classifier for Machine Learning on Embedded Platforms

Electronics (Switzerland), 2021
Darshika G Perera
exaly  

Embedded Machine Learning

2011
Ian H. Witten, Eibe Frank, Mark A. Hall
openaire   +1 more source

Knowledge-embedded machine learning and its applications in smart manufacturing

Journal of Intelligent Manufacturing, 2022
Farzam Farbiz, Mohamed Salahuddin Habibullah, Brahim Hamadicharef   +2 more
exaly