scispace - formally typeset
Search or ask a question
Topic

Hybrid neural network

About: Hybrid neural network is a research topic. Over the lifetime, 1305 publications have been published within this topic receiving 18223 citations.


Papers
More filters
Book ChapterDOI
01 Jan 2000
TL;DR: A hybrid neural network approach is presented to predict radio propagation characteristics and multiuser interference and to evaluate their combined impact on throughput, latency and information loss in third-generation (3G) wireless networks.
Abstract: A hybrid neural network approach is presented to predict radio propagation characteristics and multiuser interference and to evaluate their combined impact on throughput, latency and information loss in third-generation (3G) wireless networks. The three performance parameters influence the quality of service (QoS) for multimedia services for 3G networks. These networks are based on hierarchical cell structures and operate in mobile urban and indoor environments with service demands emanating from diverse traffic sources. Candidate radio interfaces for these networks employ a form of wideband CDMA.

2 citations

Proceedings ArticleDOI
27 Nov 1995
TL;DR: This paper presents the prototype implementation of a hybrid neural network expert system shell, aimed at preserving semantic structure of the expert system rules whilst incorporating learning capability of neural networks into the inference mechanism.
Abstract: This paper presents the prototype implementation of a hybrid neural network expert system shell. The shell, structured around the concept of "network element", is aimed at preserving semantic structure of the expert system rules whilst incorporating learning capability of neural networks into the inference mechanism. Using this architecture, every rule of the knowledge base is represented by a one or two-layer neural network element. These network elements are dynamically linked up to form the rule-tree during inference process. Furthermore, the firing of netels emulate opportunistic decision making process, which is typical of human decision makers. Finally, the system is also able to adjust its inference strategy according to different users and situations.

2 citations

Journal Article
TL;DR: A new hybrid neural network for image compression, in which the hybrid genetic algorithm and BP algorithm approach are used to train the weight vector, which shows high compression ratio, high ratio of signal vs noise, low errors of coding, high decoding speed and fine resuming effect on subject.
Abstract: This paper shows a new hybrid neural network for image compression, in which the hybrid genetic algorithm and BP algorithm approach are used to train the weight vector. So its convergent speed and precision are improved greatly. The results of test with this method show high compression ratio, high ratio of signal vs noise, low errors of coding, high decoding speed and fine resuming effect on subject.

2 citations

Book ChapterDOI
13 Dec 2018
TL;DR: A novel hybrid 2D and 3D convolution based recurrent neural network for video-based person re-id task, which can simultaneously make use of the local short-term fast-varying motion information and the global long-term spatial and temporal information.
Abstract: Video-based person re-identification (re-id), which aims to match people through videos captured by non-overlapping camera views, has attracted lots of research interest recently. In this paper, we propose a novel hybrid 2D and 3D convolution based recurrent neural network for video-based person re-id task, which can simultaneously make use of the local short-term fast-varying motion information and the global long-term spatial and temporal information. Specifically, the 3D convolutional module is able to explore the local short-term fast-varying motion information, while the recurrent layer performed can learn global long-term spatial and temporal information. We evaluate the proposed hybrid neural network on the publicly available PRID 2011, iLIDS-VID and MARS multi-shot pedestrian re-identification datasets, and the experiment results demonstrate the effectiveness of our approach on the task of video-based person re-id.

2 citations


Network Information
Related Topics (5)
Artificial neural network
207K papers, 4.5M citations
89% related
Feature extraction
111.8K papers, 2.1M citations
88% related
Fuzzy logic
151.2K papers, 2.3M citations
85% related
Convolutional neural network
74.7K papers, 2M citations
84% related
Deep learning
79.8K papers, 2.1M citations
83% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20233
20228
2021128
2020119
2019104
201863