GitLab

中煤项目人员值班接口

CrowdHMT Middleware Group, front-end development group

CrowdHMT Middleware Group, front-end development group

当今世界，计算机智能化的程度越来越高，而计算机视觉的应用也越来越广泛，从最开始的识别物品到人脸识别的动态观察，计算机能识别的图像越来越复杂化，动态化，模糊化，这都离不开深度学习算法。我们小组使用YOLO模型来训练计算机获得识别飞机的能力，如果飞机能够被迅速而准确的识别将对我们产生巨大的帮助。

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).

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).

Transport messages or pictures on devices with ros2 installed. It can be between different nodes on the same device or on different devices.

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。