Deep learning and its applications to machine health monitoring
Abstract Since 2006, deep learning (DL) has become a rapidly growing research direction,
redefining state-of-the-art performances in a wide range of areas such as object recognition …
redefining state-of-the-art performances in a wide range of areas such as object recognition …
New avenues in opinion mining and sentiment analysis
New Avenues in Opinion Mining and Sentiment Analysis Page 1 New Avenues in Opinion
Mining and Sentiment Analysis Erik Cambria, Member, IEEE, Björn Schuller, Member, IEEE …
Mining and Sentiment Analysis Erik Cambria, Member, IEEE, Björn Schuller, Member, IEEE …
[LIBRO][B] Data-driven science and engineering: Machine learning, dynamical systems, and control
SL Brunton, JN Kutz - 2022 - books.google.com
Data-driven discovery is revolutionizing how we model, predict, and control complex
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …
[PDF][PDF] Study of variants of extreme learning machine (ELM) brands and its performance measure on classification algorithm
JS Manoharan - Journal of Soft Computing Paradigm (JSCP), 2021 - scholar.archive.org
Recently, the feed-forward neural network is functioning with slow computation time and
increased gain. The weight vector and biases in the neural network can be tuned based on …
increased gain. The weight vector and biases in the neural network can be tuned based on …
What's hidden in a randomly weighted neural network?
Training a neural network is synonymous with learning the values of the weights. By
contrast, we demonstrate that randomly weighted neural networks contain subnetworks …
contrast, we demonstrate that randomly weighted neural networks contain subnetworks …
Broad learning system: An effective and efficient incremental learning system without the need for deep architecture
CLP Chen, Z Liu - IEEE transactions on neural networks and …, 2017 - ieeexplore.ieee.org
Broad Learning System (BLS) that aims to offer an alternative way of learning in deep
structure is proposed in this paper. Deep structure and learning suffer from a time …
structure is proposed in this paper. Deep structure and learning suffer from a time …
The deep learning vision for heterogeneous network traffic control: Proposal, challenges, and future perspective
Recently, deep learning, an emerging machine learning technique, is garnering a lot of
research attention in several computer science areas. However, to the best of our …
research attention in several computer science areas. However, to the best of our …
Fusing audio, visual and textual clues for sentiment analysis from multimodal content
A huge number of videos are posted every day on social media platforms such as Facebook
and YouTube. This makes the Internet an unlimited source of information. In the coming …
and YouTube. This makes the Internet an unlimited source of information. In the coming …
Data-driven ship digital twin for estimating the speed loss caused by the marine fouling
Ship** is responsible for approximately the 90% of world trade leading to significant
impacts on the environment. As a consequence, a crucial issue for the maritime industry is to …
impacts on the environment. As a consequence, a crucial issue for the maritime industry is to …
Stacked broad learning system: From incremental flatted structure to deep model
The broad learning system (BLS) has been proved to be effective and efficient lately. In this
article, several deep variants of BLS are reviewed, and a new adaptive incremental …
article, several deep variants of BLS are reviewed, and a new adaptive incremental …