Lijuan Huang1, Xianyi Liu2, Jinping Liu2,*, Pengfei Xu2,*
CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.068818
- 10 November 2025
Abstract The ubiquity of mobile devices has driven advancements in mobile object detection. However, challenges in multi-scale object detection in open, complex environments persist due to limited computational resources. Traditional approaches like network compression, quantization, and lightweight design often sacrifice accuracy or feature representation robustness. This article introduces the Fast Multi-scale Channel Shuffling Network (FMCSNet), a novel lightweight detection model optimized for mobile devices. FMCSNet integrates a fully convolutional Multilayer Perceptron (MLP) module, offering global perception without significantly increasing parameters, effectively bridging the gap between CNNs and Vision Transformers. FMCSNet achieves a delicate balance between computation… More >
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