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Multilevel Network Modeling to Achieve Cross Layer Mechanisms [chapter]

M. Issoufou Tiado, R. Dhaou, A.-L. Beylot
2006 IFIP International Federation for Information Processing  
A new way to improve the performance of ad hoc networks consists in using cross layer mechanisms. Currently, several protocols have demonstrated some reachable performance gain.  ...  A cross-layer conceptual model is composed of: cross-layer interaction models and interactions description arrays.  ...  The model aims to show additional subsystems due to interactions and to explicit internal cross-layer mechanisms.  ... 
doi:10.1007/0-387-31173-4_10 fatcat:lpyuevgghfdjdckmitta7prcyy

Multilevel Feature Exploration Network for Image Superresolution

Xinbo Liu, Ling Wang, Xinyu Chen, Yuqing Liu, Jianping Gou
2022 Scientific Programming  
Specially, we design an encoder-decoder architecture to concentrate on structural information from different levels and devise a spatial attention mechanism to address the inherent correlation among features  ...  In this paper, we find that the hierarchical design can effectively restore the structural information and devise a multilevel feature exploration network for image SR (MFSR).  ...  Multiscale dense cross network (MDCN) upgrades the MSRN and achieves state-of-the-art image SR performance.  ... 
doi:10.1155/2022/2014627 fatcat:uxdg3zenbfg45bfokcbvdnlari

Deep Learning based Weighted Feature Fusion Approach for Sentiment Analysis

Mohd Usama, Wenjing Xiao, Belal Ahmad, Jiafu Wan, Mohammad Mehedi Hassan, Abdulhameed Alelaiwi
2019 IEEE Access  
Moreover passing features from one layer to another layer within the network and one network to another network have done.  ...  Multilevel features are from different layers of the same network, and multitype features are from different network architectures.  ...  ACKNOWLEDGMENT The authors are grateful to King Saud University, Riyadh, Saudi Arabia for funding this work through Researchers Supporting Project number RSP-2019/18.  ... 
doi:10.1109/access.2019.2940051 fatcat:ph6f7yo53bamnhx62va5ttv7am

Dense Convolutional Network and Its Application in Medical Image Analysis

Tao Zhou, XinYu Ye, HuiLing Lu, Xiaomin Zheng, Shi Qiu, YunCan Liu, Chen Li
2022 BioMed Research International  
Dense convolutional network (DenseNet) is a hot topic in deep learning research in recent years, which has good applications in medical image analysis.  ...  introduced; second, the development of DenseNet is summarized and analyzed from five aspects: broaden DenseNet structure, lightweight DenseNet structure, dense unit, dense connection mode, and attention mechanism  ...  Attention mechanism introduced in transition layer has multilevel attention mechanism and multidimensional spatial attention mechanism with spatial attention gating.  ... 
doi:10.1155/2022/2384830 pmid:35509707 pmcid:PMC9060995 fatcat:7jp3tmtph5hk5gthgcomeccnte

Multilevel Attention Residual Neural Network for Multimodal Online Social Network Rumor Detection

Zhuang Wang, Jie Sui
2021 Frontiers in Physics  
In this article, we propose a multimodal online social network rumor detection model based on the multilevel attention residual neural network (MARN).  ...  First, the features of text and image are extracted by Bert and ResNet-18, respectively, and the cross-attention residual mechanism is used to enhance the representation of images with a text vector.  ...  Building Model Framework We propose a multimodal online social network rumor detection model based on the multilevel attention residual mechanism.  ... 
doi:10.3389/fphy.2021.711221 fatcat:kiqkynv4yrevjj7wrrjdd4dovu

Gated Recurrent Multiattention Network for VHR Remote Sensing Image Classification

Boyang Li, Yulan Guo, Jungang Yang, Longguang Wang, Yingqian Wang, Wei An
2021 IEEE Transactions on Geoscience and Remote Sensing  
Because informative features generally occur at multiple stages in a network (i.e., local texture features at shallow layers and global profile features at deep layers), we use multilevel attention modules  ...  In this article, we propose a gated recurrent multiattention neural network (GRMA-Net) to address these problems.  ...  Compared to BAM, our network (GRMA-NetResNet18) achieves much better performance with a comparable model size. E.  ... 
doi:10.1109/tgrs.2021.3093914 fatcat:srynjanpo5dwnebepktnmzw2wu

Video Dialog via Progressive Inference and Cross-Transformer

Weike Jin, Zhou Zhao, Mao Gu, Jun Xiao, Furu Wei, Yueting Zhuang
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
Some more advanced methods utilize hierarchical structure, attention and memory mechanisms, which still lack an explicit reasoning process.  ...  Video dialog is a new and challenging task, which requires the agent to answer questions combining video information with dialog history.  ...  A hierarchical LSTM network is added to model the dialog history. • LF+, HRE+ and MN+ methods extend three image dialog models (Das et al., 2017a) by utilizing a LSTM network to encode the video information  ... 
doi:10.18653/v1/d19-1217 dblp:conf/emnlp/JinZGXWZ19 fatcat:n2ssxxb2l5c5vmkxe2tf54qwha

E3SN: Efficient End-to-End Siamese Network for Video Object Segmentation

Meng Lan, Yipeng Zhang, Qinning Xu, Lefei Zhang
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
Such an optimization facilitates the training of the entire model in an end-to-end manner.  ...  This paper proposes an efficient end-to-end Siamese network for VOS. In particular, a supervised sampling strategy is designed to optimize the training procedure.  ...  ., 2018] proposes a modulator network trained to manipulate the intermediate layers of the segmentation network. RGMP [Oh et al., 2018] introduces a deep Siamese encoder-decoder network.  ... 
doi:10.24963/ijcai.2020/98 dblp:conf/ijcai/LanZXZ20 fatcat:pn75ngowgndhjldq3oz2vax7fq

HARC-New Hybrid Method with Hierarchical Attention Based Bidirectional Recurrent Neural Network with Dilated Convolutional Neural Network to Recognize Multilabel Emotions from Text

Md Shofiqul Islam, Mst Sunjida Sultana, Mr Uttam Kumar, Jubayer Al Mahmud, SM Jahidul Islam
2021 Jurnal Ilmiah Teknik Elektro Komputer dan Informatika  
The main goals of this proposed technique are to use deep learning approaches to identify multilevel textual sentiment with far less time and more accurate and simple network structure training for better  ...  In this analysis, the proposed new hybrid deep learning HARC model architecture for the recognition of multilevel textual sentiment that combines hierarchical attention with Convolutional Neural Network  ...  A hierarchical system to an attentive layer of this hybrid model has the advantage of a less training time as well as a clear network structure to achieve a good output, in comparison with an attentive  ... 
doi:10.26555/jiteki.v7i1.20550 fatcat:xnes4y6p2fawfcfiuxecfcu2ru

Global Context-Based Multilevel Feature Fusion Networks for Multilabel Remote Sensing Image Scene Classification

Xin Wang, Lin Duan, Chen Ning
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
term the global context-based multilevel feature fusion network.  ...  Experimental results demonstrate that the proposed method is superior to some popular networks for multilabel RS image scene classification.  ...  To this end, we plan to introduce attention mechanisms into our network, and before this, here we review the related works, including attention mechanisms and long-range dependency modeling, at first.  ... 
doi:10.1109/jstars.2021.3122464 fatcat:iumvszpu25dszdgp5fkpxqqudq

Research on Multilevel Classification of High-Speed Railway Signal Equipment Fault Based on Text Mining

Fan Gao, Fan Li, Zhifei Wang, Wenqi Ge, Xinqin Li
2021 Journal of Electrical and Computer Engineering  
In the multilevel classification model, the single-layer classification model was designed based on stacking integrated learning idea; the recurrent neural network BiGRU and BiLSTM were used as primary  ...  learners, and the weight combination calculation method was designed for secondary learners, and k-fold cross verification was used to train the stacking model.  ...  To avoid the overfitting problem caused by the model trained from the training set and to train multiple single-layer classification models and achieve the purpose of producing multiple prediction results  ... 
doi:10.1155/2021/7146435 doaj:12e9f815e34d4b6788726d22fe0e566b fatcat:wm77pznu4rfkxp6d33rq4ezwri

HDFNet: Hierarchical Dynamic Fusion Network for Change Detection in Optical Aerial Images

Yi Zhang, Lei Fu, Ying Li, Yanning Zhang
2021 Remote Sensing  
Comprehensive experiments are conducted on two benchmark datasets, LEBEDEV and LEVIR-CD, to verify the effectiveness of the proposed method and the experimental results show that our model achieves state-of-the-art  ...  To deal with these problems, we design a hierarchical dynamic fusion network (HDFNet) to implement the optical aerial image-change detection task.  ...  Multilevel Supervision As shown in Figure 3 , we use the multilevel supervision (MS) strategy to supervise multiple hidden layer features.  ... 
doi:10.3390/rs13081440 fatcat:ox2oot42pjcybpgehvbwst56ei

Suppress and Balance: A Simple Gated Network for Salient Object Detection [article]

Xiaoqi Zhao, Youwei Pang, Lihe Zhang, Huchuan Lu, Lei Zhang
2020 arXiv   pre-print
With the help of multilevel gate units, the valuable context information from the encoder can be optimally transmitted to the decoder.  ...  In this work, we propose a simple gated network (GateNet) to solve both issues at once.  ...  Without adding more cross-modal fusion techniques, or using other tracking or detection models, our GateNet can achieve competitive performance with most zero-shot vos methods.  ... 
arXiv:2007.08074v3 fatcat:svsnstvdzzbxthcfcoliugblku

AttaNet: Attention-Augmented Network for Fast and Accurate Scene Parsing [article]

Qi Song and Kangfu Mei and Rui Huang
2021 arXiv   pre-print
In this paper, we propose a new model, called Attention-Augmented Network (AttaNet), to capture both global context and multilevel semantics while keeping the efficiency high.  ...  Two factors have proven to be very important to the performance of semantic segmentation models: global context and multi-level semantics.  ...  To achieve high accuracy, segmentation models need to generate features with global context information and multilevel semantics, both of which are known to be important factors in scene parsing.  ... 
arXiv:2103.05930v1 fatcat:icpiordlujbz3hkfhjhprp7kdy

Multilevel Hierarchical Network with Multiscale Sampling for Video Question Answering [article]

Min Peng, Chongyang Wang, Yuan Gao, Yu Shi, Xiang-Dong Zhou
2022 arXiv   pre-print
While most existing approaches ignore the visual appearance-motion information at different temporal scales, it is unknown how to incorporate the multilevel processing capacity of a deep learning model  ...  Targeting these issues, this paper proposes a novel Multilevel Hierarchical Network (MHN) with multiscale sampling for VideoQA.  ...  Therein, the feature output at the last pooling layer of each network is used.  ... 
arXiv:2205.04061v1 fatcat:63ekqxvs7vbcbbx5wb7ip62joq
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