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Several baselines for online adaptation of semantic segmentation. Architectures supported: Deeplabv2 with VGG-16, ERFNet, RFNet with Resnet-18 (Updating). Baselines including: BN Adapting, Tent, Pseudo Label, Ground Truth, CoTTA, etc. (Updating).
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采用硬件描述语言Verilog HDL完成数字图像识别。数字图像识别在传统处理器上（如CPU、GPU等）得到了非常有效地发展，精确度一度达到100%，这得益于现有深度学习框架提供的成熟神将网络算法，而在如FPGA，ASIC等定制化设备上的深度学习还存在开发周期长，程序语言门槛较高等困难，将深度学习部署在这些终端设备上还有待的发展。该项目是借助Verilog硬件描述语言在FPGA上完成的卷积神经网络对数字图像识别进行识别。
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