Incremental small sample target detection method based on meta-learning
A target detection, small sample technology, applied in the field of incremental small sample target detection based on meta-learning, can solve the problems of training time overhead, basic category data storage and privacy, etc., to achieve less sample demand, data privacy protection, data privacy protection Effect
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[0045] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is carried out on the premise of the technical solution of the present invention, and detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.
[0046] Such as figure 1 As shown, the present invention proposes an incremental small-sample target detection method based on meta-learning, comprising the following steps:
[0047] 1) Feature extraction step: Given the initial image, after random cropping, flipping and other data enhancement methods and normalization operations, extract the abstract features of the image as the input of the feature extractor;
[0048] 2) Target positioning step: Target positioning includes three parallel working ends, which are heat map end, size end and compensation end. The three working ends all t...
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