FPGA-Based Implementation of Stochastic Configuration Network for Robotic Grasping Recognition
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3012819
Abstract: Precise and rapid grasping recognition based on machine vision is one of the challenging problems for intelligent robots. As a nonlinear network for recognition, the stochastic configuration network (SCN) is considered as a promising method… read more here.
Keywords: robotic grasping; grasping recognition; recognition; network ... See more keywords
Stochastic Configuration Networks: Fundamentals and Algorithms
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2017.2734043
Abstract: This paper contributes to the development of randomized methods for neural networks. The proposed learner model is generated incrementally by stochastic configuration (SC) algorithms, termed SC networks (SCNs). In contrast to the existing randomized learning… read more here.
Keywords: networks fundamentals; configuration; configuration networks; fundamentals algorithms ... See more keywords
2-D Stochastic Configuration Networks for Image Data Analytics
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DOI: 10.1109/tcyb.2019.2925883
Abstract: Stochastic configuration networks (SCNs) as a class of randomized learner model have been successfully employed in data analytics due to its universal approximation capability and fast modeling property. The technical essence lies in stochastically configuring… read more here.
Keywords: image data; data analytics; configuration networks; image ... See more keywords
Hierarchical-Bayesian-Based Sparse Stochastic Configuration Networks for Construction of Prediction Intervals.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3053306
Abstract: To address the architecture complexity and ill-posed problems of neural networks when dealing with high-dimensional data, this article presents a Bayesian-learning-based sparse stochastic configuration network (SCN) (BSSCN). The BSSCN inherits the basic idea of training… read more here.
Keywords: sparse stochastic; prediction intervals; prediction; based sparse ... See more keywords
Multi-Task Learning Based on Stochastic Configuration Neural Networks
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Bioengineering and Biotechnology"
DOI: 10.3389/fbioe.2022.890132
Abstract: When the human brain learns multiple related or continuous tasks, it will produce knowledge sharing and transfer. Thus, fast and effective task learning can be realized. This idea leads to multi-task learning. The key of… read more here.
Keywords: configuration neural; task learning; stochastic configuration; multi task ... See more keywords