An Improved Dual-Channel Network to Eliminate Catastrophic Forgetting

2020 ◽  
pp. 1-11
Author(s):  
Dongbo Liu ◽  
Zhenan He ◽  
Dongdong Chen ◽  
Jiancheng Lv
Keyword(s):  
Channel Network ◽  
Dual Channel

Deformable MR-CT Image Registration Using an Unsupervised, Dual-Channel Network for Neurosurgical Guidance

2021 ◽  
pp. 102292
Author(s):  
R. Han ◽  
C.K. Jones ◽  
J. Lee ◽  
P. Wu ◽  
P. Vagdargi ◽  
...  
Keyword(s):  
Image Registration ◽  
Ct Image ◽  
Channel Network ◽  
Dual Channel

Performance Comparison of Carrier Sense Random Packet CDMA and Partitioned Slot Reservation Packet CDMA

2014 ◽  
Vol 687-691 ◽  
pp. 2684-2688
Author(s):  
Chuan Bao Du ◽  
Hou De Quan ◽  
Pei Zhang Cui
Keyword(s):  
Resource Utilization ◽  
Packet Transmission ◽  
Network Throughput ◽  
Utilization Efficiency ◽  
Control Channel ◽  
Channel Network ◽  
Channel Networks ◽  
Dual Channel ◽  
Carrier Sense ◽  
Resource Utilization Efficiency

The Dual-Channel Network proposed in our previous work can improve the code resource utilization efficiency. Carrier Sense Random Packet (CSRP) CDMA and Partitioned Slot Reservation Packet (PSRP) CDMA were proposed for enhancing the control channel interference resistance of Dual-Channel Networks. In this paper, we investigate CSRP-CDMA and PSRP-CDMA, and derive the performance analytic models by taking into account both intra-cluster MAI and inter-cluster MAI. The models provide the expressions of packet transmission probability and normalized network throughput. Furthermore, the probability of packet successful transmission and the throughput performance are compared between the two protocols. Finally, we analyse the influence on the network performance with spread spectrum gains and network scale. The numerical results show that, normalized network throughput of PSRP-CDMA outperforms CSRP-CDMA by 20% to improving the code resource utilization efficiency of control channel of Dual-Channel Networks.

Landslide Detection of High-Resolution Satellite Images using Asymmetric Dual-Channel Network

2021 ◽  
Author(s):  
Yaohui Liu ◽  
Wenzhuo Zhang ◽  
Xiaoxian Chen ◽  
Mingyang Yu ◽  
Yingjun Sun ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Channel Network ◽  
Dual Channel ◽  
High Resolution Satellite Images

Visual-Semantic Dual Channel Network for Visual Question Answering

2021 ◽  
Author(s):  
Xin Wang ◽  
Qiaohong Chen ◽  
Ting Hu ◽  
Qi Sun ◽  
Yubo Jia
Keyword(s):  
Question Answering ◽  
Channel Network ◽  
Visual Question Answering ◽  
Dual Channel

scholarly journals Footballer Action Tracking and Intervention Using Deep Learning Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Guanghui Yang ◽  
Lijun Wang ◽  
Xiaofeng Xu ◽  
Jixiang Xia
Keyword(s):  
Learning Algorithm ◽  
Experimental Testing ◽  
Texture Features ◽  
World Cup ◽  
Channel Network ◽  
Dual Channel ◽  
Deep Learning Algorithm ◽  
Wide Range ◽  
Performance Results ◽  
Fully Connected

Fédération Internationale de Football Association is the governing body of the football world cup. The international tournament of football requires extensive training of all football players and athletes. In the training process of footballers, players and coaches recognize the training actions completed by footballers. The training actions are compared with standard actions, calculate losses, and scientifically intervene in the training processes. This intervention is important for better results during the training sessions. Coaches must determine and confirm that every action performed by the footballers meets the minimum standards. It is because the actions of individual players are performed quickly; as a result, the coach’s eye may not produce accurate results as human activities are prone to errors. Therefore, this paper designs and develops a footballer’s motion and gesture recognition and intervention algorithm using a convolutional neural network (CNN). In this proposed algorithm, initially, texture features and HSV features of the footballer’s posture image are extracted and then a dual-channel CNN is constructed. Each characteristic is extracted separately, and the output of the dual-channel network is combined. Finally, the obtained results are passed from a fully connected CNN to estimate and construct the posture image of the footballer. This article performs experimental testing and comparative analysis on a wide range of data and also conducts ablation studies. The experimental work shows that the proposed algorithm achieves better performance results.

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