代码-《深度学习之PyTorch物体检测实战》. Contribute to panda781022/Detection-PyTorch-Notebook development by creating an account on GitHub.
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Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Co...
《深度学习之PyTorch物体检测实战》是一本详细介绍如何利用PyTorch框架进行物体检测的实用书籍。书中通过DetectionPyTorchNotebook代码的讲解,系统地介绍了目标检测领域的基本概念、常用数据集的处理方法以及各种经典物体检测模型的实现原理和代码实践。读者可以通过学习这
The majority of the lab content is based on Jupyter Notebook, Python and PyTorch. The workshop details are available via the KDD'19 workshop webpage under the following external link. Running the Notebook Reference The lab is inspired by our work "Detection of Accounting Anomalies in the ...
代码-《深度学习之PyTorch物体检测实战》. Contribute to changhong2013/Detection-PyTorch-Notebook development by creating an account on GitHub.