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深度学习，模糊图像清晰化

于 2022-07-21 发布文件大小:3.20 MB

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代码说明：

------------| EnhanceNet | ------------This is a pre-trained reference implementation of ENet-PAT from "EnhanceNet:Single Image Super-Resolution through Automated Texture Synthesis" for amagnification ratio of 4.It comes with a script which takes care of installing all necessary packagesinside a virtual environment, i.e. all installations take place inside thefolder and can be simply uninstalled by deleting the folder. Advanced usersmay install the packages directly (see FAQ section).Please note that the code has only been tested on Linux and OS/X.If you use this code as part of a publication, please cite:@inproceedings{enhancenet, title={{EnhanceNet}: Single Image Super-Resolution through Automated Texture Synthesis}, author={Sajjadi, Mehdi~S.~M. and Sch{"o}lkopf, Be

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2020-06-17 17:40:03下载

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2021-05-06下载

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2019-08-09下载

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2020-07-04 10:39:50下载

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main
说明：使用openmv实现人脸识别。。。。。。。。。。。。。。。。。。(Face recognition is a kind of biometric technology based on facial feature information. A series of related technologies, also known as portrait recognition and face recognition, that use cameras or cameras to collect images or video streams containing faces, and automatically detect and track faces in the images, and then perform face recognition on the detected faces.)

2020-11-22 21:01:13下载

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python 验证码识别:示例源码
验证码识别

2019-02-25下载

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autocode
说明：在高斯噪声下，使用深度学习进行符号调制，画出星座图(Under Gauss's noise, we use deep learning to make symbol modulation and draw a constellation)

2017-12-08 23:31:44下载

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SVM-timeseries
基于SVM的时序序列预测，用python实现，内附测试数据，方便可用。(SVM prediction based on a timing sequence with python to achieve, enclosing the test data to facilitate available.)

2021-03-27 09:39:12下载

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MobileNet-master
我们提供一类称为MobileNets的高效模型，用于移动和嵌入式视觉应用。?MobileNets是基于一个流线型的架构，它使用深度可分离的卷积来构建轻量级的深层神经网络。我们引入两个简单的全局超参数，在延迟度和准确度之间有效地进行平衡。这两个超参数允许模型构建者根据问题的约束条件，为其应用选择合适大小的模型。我们进行了资源和精度权衡的广泛实验，与ImageNet分类上的其他流行的网络模型相比，MobileNets表现出很强的性能。最后，我们展示了MobileNets在广泛的应用场景中的有效性，包括物体检测，细粒度分类，人脸属性和大规模地理定位。(We provide an efficient model called MobileNets for mobile and embedded vision applications. MobileNets is based on a streamlined architecture that USES deep separable convolution to build a lightweight deep neural network. We introduce two simple global hyperparameters to effectively balance the delay and accuracy. These two hyperparameters allow the model builder to select an appropriate size model for its application based on the constraints of the problem. We conducted extensive experiments on resource and precision tradeoffs, and MobileNets showed strong performance compared with other popular network models on the ImageNet classification. Finally, we demonstrate the effectiveness of MobileNets in a wide range of application scenarios, including object detection, fine-grained classification, face attributes, and large-scale geographic localization.)

2018-09-26 18:51:51下载

积分：1

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