The invention discloses a heterogeneous convolution-based multi-core iterative RPN target detection method. The method comprises the steps of receiving to-be-detected image data; performing graying and local binarization data enhancement processing on the image data to obtain processed image data; inputting the processed image data into a heterogeneous convolutional network for feature extractionto obtain a feature map; inputting the feature map into a multi-scale feature extraction network, realizing feature extraction of different scales, and obtaining a target feature map; inputting the target feature map into an RIR target detection network to obtain a plurality of region candidate boxes; obtaining a target score corresponding to each region candidate box according to the non-maximumsuppression function, and obtaining a region suggestion window according to a preset score threshold; and according to the full convolutional network layer and the normalized exponential function classifier, classifying the region suggestion windows to obtain a classification result, an image category and a confidence score. By applying the embodiment of the invention, the problems of low runningspeed, poor small target detection effect and the like are effectively solved.
Heterogeneous convolution-based multi-core iterative RPN target detection method