Face detection method based on hierarchical network and cluster merging
A face detection and grading network technology, applied in the field of face recognition, can solve the problems of low robustness to changes in posture, complex network design, loss of face information, etc., to avoid missed face detection and simplify the network structure. , the effect of accelerated time
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[0032] The technical solutions of the present invention will be further described in detail below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.
[0033] Such as figure 1 As shown, this embodiment provides a face detection method based on hierarchical network and clustering merging, and the process can be divided into the following general steps:
[0034] Step 1: Divide the convolutional neural network into two-level networks, the first-level network contains three convolutional layers, and the second-level network contains five convolutional layers;
[0035] Step 2: Preprocess the original input image, and then generate a series of sub-images to be detected through a multi-resolution sliding window with seven levels of resolution;
[0036] Step 3: Collect training samples, pre-train the first-level network, after the pre-training is complet...
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Abstract
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