Additionally, we introduce a post-processing method that combines the target information and target contours to distinguish overlapping nuclei and generate an instance segmentation image.
To address this issue, we propose a Voting-Stacking ensemble strategy, which employs three Inception networks as base learners and integrates their outputs through a voting ensemble.
The core idea of this design is to bridge the outputs of the previous convolution layers through skip connections for channel weights generation.
However, in real applications, small traffic-signs recognition is still challenging.
Ranked #1 on Traffic Sign Recognition on Tsinghua-Tencent 100K
In addition, we introduce an additional global graph structure network to compensate for the relative information of the individual points in the graph structure network.
Therefore, through calibration of an ACS we want to find not only the relative poses between the cameras but also the positions of the joints in the ACS.
Many efforts have been devoted to develop alternative methods to traditional vector quantization in image domain such as sparse coding and soft-assignment.