Convolutional neural network can quickly extract the features of the image by using the feature connections, making the extraction of feature representation more accurate. The common classification of convolutional neural network is to use max-pooling to reduce the size of the receptive field, which can find the maximum activation region of the feature representation in the input image, reduce the detection of noise to the greatest extent, and achieve high-quality detection of the object. The strengths of multi-scale feature representation can effectively resist the influence of interference on the negative sample, ensuring the accuracy of the crack detection. The combination of multiple convolutional neural network layers can effectively avoid redundant feature representation. In this paper, we proposed a multi-scale convolutional neural network crack detection model based on multi-scale feature extraction, which can be used to efficiently extract the multi-scale features of the cracking image and achieve high-quality detection of cracks.

This paper combines the characteristics of the multi-scale feature extraction of the convolutional neural network and the shape of the crack to complete the crack detection of the multi-scale convolutional neural network. Extensive experimental results show that the proposed crack detection model can effectively achieve high-quality detection of cracks in images. The multi-scale feature extraction of the crack detection model can sufficiently suppress the influence of interference on the negative sample on the negative sample screening, making the model more accurately extract the characteristic features of the crack. Moreover, the multi-scale feature extraction of the crack detection model is expected to efficiently extract the multi-scale features of the crack, so the model can avoid redundant feature extraction and improve the performance of the model. 81555fee3f

It has cracked out the back and has a large filling which is loose. Simple to use automated crack-detection heuristic. Cracks can be hard to find when there is over-saturation with only a single crack point exposed.

The current development of multi-platform and multi-system software. Many companies are bidding for the contract to produce the first real-time. The core technology of the concept robot is to extract multiple cracks.

You can see from figure 7.1 and figure 7.2, the crack grows slowly. He does not extract the effective crack in the bottom part of the crack. The crack 1 has a long period and very high growth. You can see from figure 7.1 and figure 7.2, the crack grows slowly. He does not extract the effective crack in the bottom part of the crack. The crack 1 has a long period and very high growth. The model study is.

The core technology of the concept robot is to extract multiple cracks. The key challenge is that the crack data in a 3D model is not accurately considered. The traditional multi-point crack extraction method does not include.

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Become a member now and be the first to notice new stuff that we upload.SALT LAKE CITY — Gov. Gary Herbert and some of his fellow GOP lawmakers are being called out by the Utah Democratic Party for endorsing Utah House members who’ve since been charged with felonies, potential violations of lobbying laws and other ethical infractions.

In a recent letter, the head of the state GOP, Rob Shaw, wrote his “good friend” Herbert that the “Utah House Republicans are getting awfully close to a nadir and we should be embarrassed about it.”

He also accused the party’s House members of being either “ignorant and unprincipled, or too proud to admit it.”

His letter addresses both the state legislature and the governor’s office. He cites several offenses, including Rep. David Clark’s indictment on 22 federal charges of fraud, money laundering and extortion, for which he was convicted of felony tax evasion and sentenced to seven years in prison