Image recognition method and device and electronic equipment
An image recognition and image technology, applied in the field of image processing, can solve the problems of input image motion blur, low accuracy, poor recognition effect, etc., and achieve the effect of good image recognition effect, clear image, and improved image recognition accuracy.
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0032]First, refer to figure 1 An example electronic device 100 for implementing an image recognition method, device and electronic device according to an embodiment of the present invention will be described.
[0033] Such as figure 1 Shown is a schematic structural diagram of an electronic device. The electronic device 100 includes one or more processors 102, one or more storage devices 104, an input device 106, an output device 108, and an image acquisition device 110. These components pass through a bus system 112 and / or other forms of connection mechanisms (not shown). It should be noted that figure 1 The shown components and structure of the electronic device 100 are exemplary rather than limiting, and the electronic device may also have other components and structures as required.
[0034] The processor 102 can be implemented in at least one hardware form of a digital signal processor (DSP), a field programmable gate array (FPGA), and a programmable logic array (PLA)...
Embodiment 2
[0041] This embodiment provides an image recognition method, which is applied to an image recognition model. First, see figure 2 A schematic structural diagram of an image recognition model is shown. This embodiment provides a specific method of an image recognition model, which mainly includes a preprocessing network, a meta-learning network and an image recognition network. The preprocessing network is connected with the meta-learning network and the human Face recognition network connection, wherein both the meta-learning network and the pre-processing network use images as input, and the output of the meta-learning network is connected to the input of the pre-processing network, and the images are respectively input to the pre-processing network and the meta-learning network, and finally can be Get the output of the image recognition network. On the basis of the structure of this image recognition model, see image 3 A flow chart of an image recognition method is shown, ...
Embodiment 3
[0087] For the training method of the image recognition model provided in the second embodiment, the embodiment of the present invention provides an image recognition device, see Figure 8 A structural block diagram of an image recognition device shown, the device includes the following modules:
[0088] An image acquisition module 802, configured to acquire an image to be identified;
[0089] The image input module 804 is used to input the image to be recognized into the pre-trained image recognition model; wherein the image recognition model includes a preprocessing network, a meta-learning network and an image recognition network;
[0090] The meta-learning module 806 is used to generate the parameters of the preprocessing network based on the image to be recognized through the meta-learning network;
[0091] The preprocessing module 808 is used to perform deblurring processing on the image to be recognized based on the parameters generated by the meta-learning network thr...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More