Floor plan recognition method based on deep learning

A deep learning and recognition method technology, applied in the field of house type map recognition based on deep learning, can solve the problems of mixed results, low work efficiency, time-consuming and labor-intensive, etc., and achieve the effect of saving time and manpower in training and use, and the model structure is simple.

Inactive Publication Date: 2018-05-08
诸葛启航(苏州)科技有限公司
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0002] In the field of real estate, the classification of house plans is still using manual methods or simple machine-assisted methods. The work efficiency is extremely low, and the effect is also mixed.
[0003] The work efficiency of the existing method is extremely low, and the cost is extremely high. Manual-based classification is not only time-consuming and laborious, but also difficult to ensure quality, and it is also difficult to evaluate and monitor quality. It cannot adapt to the processing of massive data, and it is difficult to face big data. The challenge of the times

Method used

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with specific embodiments, and the advantages and characteristics of the present invention will become clearer along with the description. However, these embodiments are only exemplary and do not constitute any limitation to the scope of the present invention. Those skilled in the art should understand that the details and forms of the technical solutions of the present invention can be modified or replaced without departing from the spirit and scope of the present invention, but these modifications and replacements all fall within the protection scope of the present invention.

[0029] The present invention relates to a method for identifying house type diagrams based on deep learning, comprising the following steps:

[0030] (1) Collection and preprocessing of training data;

[0031] (2) Carry out model training;

[0032] (3) Use of models.

[0033] The step (1) is specifically:

[0034] (1-1) Us...

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Abstract

The invention relates to a floor plan recognition method based on deep learning. The method comprises the following steps: (1) the acquiring and preprocessing training data; (2) training a model; and(3) using the model. The method does not use manual marking, saves manpower. The model is simple in structure and is time-efficient in training and use. Multiple interfaces can be used to meet the needs of different scenarios.

Description

technical field [0001] The invention relates to a method for recognizing house type diagrams based on deep learning. Background technique [0002] In the field of real estate, the classification of floor plans still uses manual methods or simple machine-assisted methods. The work efficiency is extremely low, and the effect is also mixed. [0003] The work efficiency of the existing method is extremely low, and the cost is extremely high. Manual-based classification is not only time-consuming and laborious, but also difficult to ensure quality, and it is also difficult to evaluate and monitor quality. It cannot adapt to the processing of massive data, and it is difficult to face big data. The challenge of the times. Contents of the invention [0004] In order to overcome the defects of the prior art, the present invention provides a method for identifying house type diagrams based on deep learning. The technical solution of the present invention is: [0005] A method for ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08G06F17/30
CPCG06F16/951G06N3/084G06N3/045G06F18/214
Inventor 白峻峰张文战刘子曜苏伟杰
Owner 诸葛启航(苏州)科技有限公司
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