Crowd counting, i.e. count the number of people in a crowded visual space, is emerging as an essential research problem with public security. A key in the design of the crowd counting system is to create a stable and accurate robust model, which requires to process on the feature channels of the counting network. In this study, the authors present a featured channel enhancement (FCE) block for crowd counting. First, they use a feature extraction unit to obtain the information of each channel and encodes the information of each channel. Then use a non-linear variation unit to deal with the encoded channel information, finally, normalise the data and affixed to each channel separately. With the use of the FCE, the positive characteristic channel can be enhanced and weak or negative channel information can be suppressed. The authors successfully incorporate the FCE with two compact networks on the standard benchmarks and prove that the proposed FCE achieves promising results.

中文翻译：

---

功能频道增强，可进行人群计数

人群计数，即对拥挤的视觉空间中的人数进行计数，已成为公共安全的基本研究问题。人群计数系统设计的关键是创建一个稳定而准确的鲁棒模型，这需要在计数网络的特征通道上进行处理。在这项研究中，作者提出了一个用于人群计数的特色频道增强（FCE）块。首先，他们使用特征提取单元获得每个频道的信息并对每个频道的信息进行编码。然后使用非线性变化单元处理编码后的频道信息，最后，对数据进行归一化并分别粘贴到每个频道上。通过使用FCE，可以增强正特性信道，并且可以抑制弱或负信道信息。