Network, System and Method for Image Processing

A system of image processing, especially for coarse-to-fine recognition, comprising an input device, a processor for processing the input data, and an output device for outputting the processed data;

• wherein the processor is configured to build a computing model comprising:
• a shared convolution layer,
• a first subnet and a second subnet both subsequent to the shared convolution layer;
• wherein the first subnet comprises
• a first skipping module comprising one or more skip-dense blocks iteratively stacked with one or more transition layers;
• a first pooling layer subsequent to the first skipping module, and
• a first classification layer subsequent to the first pooling layer,
• wherein the second subnet comprises
• a second skipping module comprising one or more skip-dense blocks iteratively stacked with one or more layers;
• a second pooling layer subsequent to the second skipping module, and
• a second classification layer subsequent to the second pooling layer,
• wherein a skip-dense block of the second subnet is selected to guide a transition layer of the first subnet, and the level of the guiding skip-dense block is deeper than the level of the guided transition layer.

A method of image processing, especially for coarse-to-fine recognition, comprising the steps of:

• inputting input data to a shared convolution layer;
• outputting an output of the shared convolution layer to a first subnet and a second subnet both subsequent to the shared convolution layer;
• wherein the first subnet comprises
• a first skipping module comprising one or more skip-dense blocks iteratively stacked with one or more transition layers;
• a first pooling layer subsequent to the first skipping module, and
• a first classification layer subsequent to the first pooling layer,
• wherein the second subnet comprises
• a second skipping module comprising one or more skip-dense blocks iteratively stacked with one or more layers;
• a second pooling layer subsequent to the second skipping module, and
• a second classification layer subsequent to the second pooling layer;
• and
• selecting a skip-dense block of the second subnet to guide a transition layer of the first subnet, and the level of the guiding skip-dense block is deeper than the level of the guided transition layer.