Abstract: A sorting device comprises a sorting apparatus moving along a predetermined path and a container conveyer located below the sorting apparatus. The sorting apparatus comprises a plurality of sorting stations arranged in a predetermined path, wherein a first discharge port and a second discharge port are formed on two sides of each sorting station along the predetermined path, respectively. A plurality of containers is placed on the container conveyer and is arranged in a linear array. The direction of the linear array is the direction of the connecting line of the first discharge port and the second discharge port where the containers reciprocate, so that two of the plurality of containers are aligned with the first discharge port and the second discharge port.

Abstract: A refined segmentation system, method and device of an image shadow area are provided. The system of the present invention includes: a feature extraction network, a reverse fusion network, and a weighted fusion network. The feature extraction network includes a plurality of sampling layers which are arranged sequentially, a plurality of segmentation features of the shadow areas in the input images are obtained through the sampling layers sequentially. The reverse fusion network includes a plurality of layered reverse fusion branches, each of which includes a plurality of feature fusion layers arranged in sequence, and two input features are fused in sequence through each feature fusion layer. The weighted fusion network is configured to perform weighted fusion on outputs of the plurality of reverse fusion branches to obtain a final segmentation result of the shadow area of the input image.

Abstract: A refined segmentation system, method and device of an image shadow area are provided. The system of the present invention includes: a feature extraction network, a reverse fusion network, and a weighted fusion network. The feature extraction network includes a plurality of sampling layers which are arranged sequentially, a plurality of segmentation features of the shadow areas in the input images are obtained through the sampling layers sequentially. The reverse fusion network includes a plurality of layered reverse fusion branches, each of which includes a plurality of feature fusion layers arranged in sequence, and two input features are fused in sequence through each feature fusion layer. The weighted fusion network is configured to perform weighted fusion on outputs of the plurality of reverse fusion branches to obtain a final segmentation result of the shadow area of the input image.