As two mainstream and excellent neural networks,ResNet and DenseNet have been the main research directions of many scholars and *** paper mainly focuses on these two neural networks through a theoretical analysis,summ...
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As two mainstream and excellent neural networks,ResNet and DenseNet have been the main research directions of many scholars and *** paper mainly focuses on these two neural networks through a theoretical analysis,summary discussions,and practical *** author explains their previous advantages and disadvantages,and,as a potentially obsolete technology,whether ResNet will be better or more efficient than DenseNet in some *** final experimental results show that although ReseNet is a somewhat outdated neural network model,it still outperforms DenseNet in some *** addition,this paper provides some further optimization schemes for reference through the analysis of the two neural network *** the same time,the basic structure and algorithm principle of the two neural networks are further explained in the analysis to make it clearer for readers.
Shallow water multi-beam echo sounders(MBESs)are characterized by their high resolution and high density,and MBES data processing is a hotspot in modern marine *** Combined Uncertainty and Bathymetry Estimator(CUBE)is...
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Shallow water multi-beam echo sounders(MBESs)are characterized by their high resolution and high density,and MBES data processing is a hotspot in modern marine *** Combined Uncertainty and Bathymetry Estimator(CUBE)is the mainstream MBES data processing algorithm,although little is known about its core theories and *** this paper,the basic principle,mathematical model,key parameters,and main processing steps of CUBE are described systematically.A parameter group optimization method that combines CUBE with a surface filter is ***,an example is given that shows the steps for parameter group optimization,including selection of a typical area,parameter group testing,and comparative analysis,and the method is then applied to shallow water MBES data *** results show that the method can improve the accuracy and efficiency of automatic data processing effectively,and it is thus of engineering application value.
A swarm intelligence algorithm develops rapidly, which has solved many large scale complex problems these years. Artificial bee colony algorithm is a new swarm intelligence algorithm and gets wide attention for its su...
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ISBN:
(纸本)9781510806481
A swarm intelligence algorithm develops rapidly, which has solved many large scale complex problems these years. Artificial bee colony algorithm is a new swarm intelligence algorithm and gets wide attention for its superior performance, such as, strong global convergence, greedy heuristic search feature and quickly problem solution. The biological background is introduced briefly;By comparing bees foraging behavior with problems solution, modeling thought is given;algorithm model is introduced in detail. Then, research status quo is discussed from two aspects, improvement and application of the algorithm. Also, conclusions are given about artificial bee colony algorithm, and improvement direction and application field are put forward from the weakness analysis of algorithm.
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