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examonline-master
说明： 在线考试系统，能够支持各类功能，帮助对python语言的学习。(Online examination system can support various functions)
- 2020-07-25 20:58:42下载
- 积分：1
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Unet-train
说明： 使用python的tensorflow库进行u-net进行图像去噪(Using tensorflow Library of Python for u-net image denoising)
- 2020-12-25 11:29:06下载
- 积分：1
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qgis-earthengine-examples-master
说明： 地理信息处理和下载工具，基于QGIS 和GEE,希望对您有所帮助(based on Qgis and GEE)
- 2020-07-20 11:49:11下载
- 积分：1
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依赖库
说明： python支持库，主要用于软件测试，与软件开发，还有树莓派支持底层(Python support library, mainly for software testing, and software development, as well as raspberry pie support underlying layer)
- 2020-06-16 08:00:01下载
- 积分：1
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py-faster-rcnn-master
图像检测的算法，Faster R-CNN算法，先对整张图像进行卷积计算，然后通过感兴趣区域池化层(RoI Pooling Layer)将选择性搜索算法推荐出来的候选区域和卷积网络计算出的特征映射图进行融合，得到候选区域对应的特征矢量，这种共享卷积计算的操作极大地减少了卷积计算的次数。而且这些特征矢量的维度统一，方便后续的分类工作。通过感兴趣区域池化层处理卷积特征，并将得到的特征送往两个并行计算任务进行训练，分类和定位回归。通过这些方法和改进的框架，Fast R-CNN 用更短的训练和测试时长，取得了比 R-CNN 更好的效果(Faster R-CNN algorithm first convolutes the whole image, then fuses the candidate regions recommended by the selective search algorithm and the feature mapping maps calculated by the convolution network through the RoI Pooling Layer to get the corresponding feature vectors of the candidate regions, which greatly reduces the number of convolution calculations. Moreover, the dimension of these feature vectors is unified, which facilitates the subsequent classification work. The convolution feature is processed by the pooling layer of the region of interest, and the obtained feature is sent to two parallel computing tasks for training, classification and positioning regression. Through these methods and improved framework, Fast R-CNN uses shorter training and testing time and achieves better results than R-CNN.)
- 2020-12-11 15:39:18下载
- 积分：1
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数值分析-基于python插值函数实现以及利用maplotlib绘图
参考资料为清华大学出版社的数值分析，作者为李庆杨、王能超、易大义。 运行后可以输入任意点，程序会根据这些点实现插值函数的构造以及绘图。同时提供了一些预设点和龙格函数的点集构造方法。实现的插值方法有：牛顿插值、拉格朗日插值、三次样条插值。 在运行前必须安装numpy库和matplotlib库。
- 2021-05-07下载
- 积分：1
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SRCNN-Tensorflow
SRCNN Superresolution imteplated by tensorflow SRCNN tensorflow 实现(SRCNN Superresolution imteplated by tensorflow)
- 2020-11-28 11:19:30下载
- 积分：1
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Qt_DockWidget
windows下面使用QT显示opengl的，并且测试了tabWidget中tab垂直放置(Windows uses QT to display OpenGL and tests the vertical placement of tab in tabWidget.)
- 2020-10-18 09:47:27下载
- 积分：1
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LSTM-Human-Activity-Recognition-master
说明： 与经典的方法相比，使用具有长时间记忆细胞的递归神经网络(RNN)不需要或几乎不需要特征工程。数据可以直接输入到神经网络中，神经网络就像一个黑匣子，可以正确地对问题进行建模。其他研究在活动识别数据集上可以使用大量的特征工程，这是一种与经典数据科学技术相结合的信号处理方法。这里的方法在数据预处理的数量方面非常简单(Compared with the classical methods, the recursive neural network (RNN) with long-term memory cells does not need or almost need feature engineering. Data can be directly input into the neural network, which acts as a black box and can correctly model the problem. Other research can use a lot of Feature Engineering on activity recognition data sets, which is a signal processing method combined with classical data science and technology. The method here is very simple in terms of the number of data preprocessing)
- 2019-06-13 18:50:02下载
- 积分：1
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WIn10+Anaconda环境下安装PyTorch(避坑指南)
WIn10+Anaconda环境下安装PyTorch(避坑指南)
- 2021-05-06下载
- 积分：1
