Deep learning-based call answering and making behavior analysis method and equipment

A technology for making calls and deep learning, applied in the field of image recognition, can solve problems such as affecting the use of the camera, the camera does not have an automatic cleaning lens, affecting the camera monitoring, etc., to facilitate the cleaning of the camera lens, solve the inability to automatically clean the lens, improve practical sexual effect

Inactive Publication Date: 2022-08-02
苏州数独智能科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the current camera does not have the function of automatically cleaning the lens. In special weather, water mist or water droplets will appear on the lens of the camera, which will affect the monitoring of the camera. After a long time of use, dust will adhere to the lens of the camera, which will affect the use of the camera. , it needs to be wiped in time; therefore, a method and equipment for analyzing the behavior of making and receiving calls based on deep learning are proposed to solve the above problems

Method used

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  • Deep learning-based call answering and making behavior analysis method and equipment
  • Deep learning-based call answering and making behavior analysis method and equipment
  • Deep learning-based call answering and making behavior analysis method and equipment

Examples

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Embodiment 1

[0033] see Figure 1-6 As shown in the figure, a deep learning method and device for analyzing the behavior of making and receiving calls, including the following steps:

[0034] S1: The system automatically learns visual features to represent behaviors from image data of a large number of people answering calls through a deep convolutional neural network, and establishes a database;

[0035] S2: Real-time monitoring of the gas station through the image acquisition device, namely the camera, captures and monitors the movements of the characters, and transmits the data to the system;

[0036] S3: Due to the effect of deep learning, the system can analyze the captured image and compare it with the database to find out whether the character is answering or not on the phone;

[0037] S4: If it is judged that the person in the gas station has the behavior of answering the phone, the system will immediately send out an alarm reminder, urging the person to stop the behavior of answeri...

Embodiment 2

[0054] see Figure 7 As shown in the comparison example 1, as another embodiment of the present invention, four mounting blocks 35 are fixed on the bottom plate 1, and mounting holes 36 are opened on the mounting blocks 35; during operation, during the installation process The base plate 1 can be mounted somewhere by means of the mounting holes 36 and bolts.

[0055] Working principle: During normal use, the first electric push rod 5 is in an extended state, the camera body 4 is at the highest position and is in a normal working state, and the cleaning mechanism is located below it will not affect the normal operation of the camera body 4. A large amount of heat will be generated in the camera body. Since the second housing 3 is in contact with the camera body 4, the heat will be transferred to the second housing 3, and then the heat will pass through the first heat sink 25 and the second heat sink 27 from the first heat dissipation hole 26. and the second heat dissipation ho...

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Abstract

The invention belongs to the field of image recognition, and particularly relates to a deep learning call answering and making behavior analysis method and device, and the method comprises the following steps: a system automatically learns visual features from the image data of a large number of people answering and making calls through a deep convolutional neural network, represents the behaviors, and builds a database; an image acquisition device, namely a camera, is used for monitoring the interior of the gas station in real time, capturing and monitoring figure forms and actions and transmitting data to the system; due to the effect of deep learning, the system can analyze the captured image and compare the image with a database; by arranging a wind wheel, the wind wheel can drive a cam to rotate, by arranging the cam and a first spring, the cam can enable a lifting plate to do reciprocating motion in the vertical direction so as to drive a sponge block to do reciprocating motion on the surface of a lens, by arranging a second spring, the sponge block can keep pressure on the lens all the time, and cleaning of the lens is achieved; and the operation is relatively convenient.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to a deep learning method and device for analyzing the behavior of making and receiving calls. Background technique [0002] In some special occasions, it is not allowed to make calls, which will cause potential safety hazards. For example, in gas stations and other places, the behavior of making calls is strictly monitored in the gas station. Once the behavior of making and receiving calls is found, the staff should immediately go to stop it. . [0003] Currently, cameras are used to monitor the gas station, and gas station staff are required to watch the surveillance video in real time and check whether people in the gas station are answering or making phone calls. [0004] However, the current camera does not have the function of automatically cleaning the lens. In special weather, water mist or water droplets will appear on the lens of the camera, which affects the monitoring o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V10/12G06V40/20G06V20/52B08B1/00F26B5/14H04N5/225H05K7/20
CPCG06V10/12G06V40/20G06V20/52F26B5/14H05K7/20H04N23/00B08B1/143B08B1/30Y02D30/70
Inventor 郑鹏博
Owner 苏州数独智能科技有限公司
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