Computer vision

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* 交感互动(例如人机互动的输入设备)
 
* 交感互动(例如人机互动的输入设备)
  
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==理论==
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*[http://mathworld.wolfram.com/Convolution.html Convolution]
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*[[Convolutional neural network|卷积神经网络]]
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*[https://cs231n.github.io/convolutional-networks/ CS231n Convolutional Neural Networks for Visual Recognition]
  
 
==项目==
 
==项目==
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计算机视觉的开源深度学习:Torch vs Caffe
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[[image:torch-vs-caffe.jpg]]
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[[文件:cvf.jpg|right]]
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*[[Torch]]
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*[[Caffe]]
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*[[TensorFlow]]
 
*[https://github.com/luispedro/mahotas Mahotas: Python Computer Vision Library]
 
*[https://github.com/luispedro/mahotas Mahotas: Python Computer Vision Library]
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*[http://libccv.org/ ccv] - a modern computer vision library
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*[[OpenFace]]
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*[[OpenCV]], [http://docs.huihoo.com/opencv/3.0/da/d60/tutorial_face_main.html 人脸识别]
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*[https://github.com/BradLarson/GPUImage2 GPUImage 2]
  
==图集==
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==ImageNet==
<gallery>
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[[文件:imagenet-logo.jpg|right]]
image:computer-vision.png|Computer Vision
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*[http://image-net.org ImageNet官网]
image:computer-vision-zh-cn.jpg|计算机视觉
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*[http://vision.stanford.edu/ Stanford Vision Lab]
image:image-processing-and-computer-vision-python-ecosystem.png|Python生态
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</gallery>
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==文档==
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*[http://docs.huihoo.com/infoq/qconbeijing/2016/day1/%E6%96%B0%E5%85%B4%E6%8A%80%E6%9C%AF%E5%8F%8A%E5%BA%94%E7%94%A8%E4%B8%93%E9%A2%98/5-4-%E4%BA%BA%E8%84%B8%E8%AF%86%E5%88%AB%E6%8A%80%E6%9C%AF%E5%9C%A8%E5%95%86%E4%B8%9A%E9%93%B6%E8%A1%8C%E7%9A%84%E5%BA%94%E7%94%A8%E5%8F%8A%E6%8C%91%E6%88%98-%E7%8E%8B%E6%99%B6.pdf 人脸识别技术在商业银行的应用及挑战]
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*[http://docs.huihoo.com/deep-learning/deeplearningsummerschool/2015/Seeing-People-with-Deep-Learning.pdf Seeing People with Deep Learning]
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*[http://docs.huihoo.com/deep-learning/deeplearningsummerschool/2015/Deep-Learning-Deep-Boltzmann-Machines.pdf Deep Learning: Deep Boltzmann Machines]
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*[http://docs.huihoo.com/gputechconf/gtc2015/S5713-Collaborative-Feature-Learning-from-Social-Media.pdf Collaborative Feature Learning from Social Media]
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*[http://docs.huihoo.com/gputechconf/gtc2015/S5474-CloudCV-Large-Scale-Distributed-Computer-Vision-as-a-Cloud-Service.pdf CloudCV: Large-Scale Computer Vision on the Cloud]
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*[http://docs.huihoo.com/gputechconf/gtc2015/S5580-Application-of-GPUs-to-Classification-Problems-Using-Deep-Learning-Architectures.pdf Application of GPUs to Classification Problems Using Deep Learning Architectures]
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*[http://docs.huihoo.com/gputechconf/gtc2015/S5577-Building-State-of-Art-Face-Processing-Pipeline-with-GPU.pdf Understand Face with GPU and beyond]
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*[http://docs.huihoo.com/gputechconf/gtc2015/S5123-Through-the-Eyes-of-a-Car-Visualizing-a-Car-Camera-System.pdf Visualizing a Car's Camera System: Computer Vision for Automotive]
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*[http://docs.huihoo.com/gputechconf/gtc2015/S5457-Maximizing-Face-Detection-Performance-on-GPUs.pdf Maximizing Face Detection Performance]
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*[http://docs.huihoo.com/gputechconf/gtc2015/S5182-The-Future-of-Human-Vision-Preferential-Augmentation-Using-GPUs.pdf The Future of Human Vision: Preferential Augmentation Using GPUs]
  
 
==图书==
 
==图书==
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*[http://book.huihoo.com/computer-vision/Computer-Vision-Ballard-and-Brown-1982.pdf 《Ballard and Brown's Computer Vision》]
 
*[http://book.huihoo.com/computer-vision/computer-vision-algorithms-and-applications-20100903-draft.pdf 《Computer Vision: Algorithms and Applications》近1000页]
 
*[http://book.huihoo.com/computer-vision/computer-vision-algorithms-and-applications-20100903-draft.pdf 《Computer Vision: Algorithms and Applications》近1000页]
  
 
==视频==
 
==视频==
 
*[https://www.youtube.com/watch?v=40riCqvRoMs 李飞飞: 我们怎么教计算机理解图片?赋予计算机视觉智能] ps: 在2007年发起了[http://www.image-net.org/ ImageNet(图片网络)]计划.
 
*[https://www.youtube.com/watch?v=40riCqvRoMs 李飞飞: 我们怎么教计算机理解图片?赋予计算机视觉智能] ps: 在2007年发起了[http://www.image-net.org/ ImageNet(图片网络)]计划.
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==课程==
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*[http://vision.stanford.edu/teaching.html 斯坦福计算机视觉课程]
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*[http://www-inst.eecs.berkeley.edu/~cs280/sp15/index.html 伯克利 CS280: Computer Vision], [http://docs.huihoo.com/computer-vision/berkeley/cs280-computer-vision 幻灯片下载]
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==厂商==
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*[https://www.azure.cn/projectoxford/vision 微软牛津计划 Computer Vision API][https://github.com/Microsoft/ProjectOxford-ClientSDK GitHub]
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*[http://www.faceplusplus.com.cn/ Face++人脸识别]
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*[http://deepglint.com/ 格灵深瞳]: 三维计算机视觉 + 深度学习,车辆识别和安防产品
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*[https://open.tuputech.com/ 图普科技]: 专注于图像识别和视觉检测
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*[http://www.sensetime.com/cn SenseTime]
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*[http://www.hiscene.com HiScene]
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*[[vision.ai]]
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*[http://cloudsightapi.com/ CloudSight]
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*[http://cloudcv.org/ CloudCV]
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*[http://www.clarifai.com/ Clarifai]
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*[http://vision.alchemy.ai/ Alchemy Vision], [http://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/alchemy-vision.html IBM AlchemyVision]
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*[https://www.imageidentify.com/ The Wolfram Language Image Identification Project]
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*[http://www.adaptive-vision.com Machine Vision Software and Libraries - Adaptive Vision]
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*[http://itseez.com/ Itseez - Computer Vision Consulting - Machine Learning]
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==图集==
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<gallery>
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image:computer-vision.png|Computer Vision
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image:computer-vision-2.png|Compuer Vision
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image:computer-vision-zh-cn.jpg|计算机视觉
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image:computer-graphics-and-computer-vision.png|计算机图形和计算机视觉
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image:image-processing-and-computer-vision-python-ecosystem.png|Python生态
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image:openface.jpg|OpenFace
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image:metamind-imagenet-accuracy.png|ImageNet精确度
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image:AVCaptureStillImageOutput-CIFaceDetector.png|人脸识别
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</gallery>
  
 
==链接==
 
==链接==
 
*[http://www.cv-foundation.org/ The Computer Vision Foundation]
 
*[http://www.cv-foundation.org/ The Computer Vision Foundation]
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*[https://github.com/jbhuang0604/awesome-computer-vision Awesome Computer Vision] [[image:awesome.png]]
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*[https://github.com/kjw0612/awesome-deep-vision Awesome Deep Vision] [[image:awesome.png]]
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*[http://ai.stanford.edu/ Stanford Artificial Intelligence Laboratory]
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*[http://vision.stanford.edu/ Stanford Computer Vision Lab]
 
*[http://bvlc.eecs.berkeley.edu/ Berkeley Vision and Learning Center]
 
*[http://bvlc.eecs.berkeley.edu/ Berkeley Vision and Learning Center]
*[http://www.sensetime.com/cn SenseTime]
 
*[http://www.hiscene.com HiScene]
 
 
*[http://cs.stanford.edu/people/karpathy/ Andrej Karpathy]、[https://github.com/karpathy Andrej @ GitHub]
 
*[http://cs.stanford.edu/people/karpathy/ Andrej Karpathy]、[https://github.com/karpathy Andrej @ GitHub]
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*[http://www.chinacloud.cn/show.aspx?id=21212&cid=17 2015深度学习回顾:ConvNet、Caffe、Torch及其他]
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*[https://www.zhihu.com/question/20672053 计算机视觉,计算机图形学和数字图像处理,三者之间的联系和区别是什么?]
  
 
[[category:artificial intelligence]]
 
[[category:artificial intelligence]]
 
[[category:computer vision]]
 
[[category:computer vision]]
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[[category:deep learning]]

2016年8月30日 (二) 15:22的版本

Wikipedia-35x35.png 您可以在Wikipedia上了解到此条目的英文信息 Computer vision Thanks, Wikipedia.

Computer vision 计算机视觉

计算机视觉是一门研究如何使机器“看”的科学,更进一步的说,就是指用摄影机和计算机代替人眼对目标进行识别、跟踪和测量等机器视觉,并进一步做图像处理,用计算机处理成为更适合人眼观察或传送给仪器检测的图像。

计算机视觉系统组成部分包括:

  • 过程控制(例如工业机器人和无人驾驶汽车)
  • 事件监测(例如图像监测)
  • 信息组织(例如图像数据库和图像序列的索引创建)
  • 物体与环境建模(例如工业检查,医学图像分析和拓扑建模)
  • 交感互动(例如人机互动的输入设备)

目录

理论

项目

计算机视觉的开源深度学习:Torch vs Caffe

Torch-vs-caffe.jpg

Cvf.jpg

ImageNet

Imagenet-logo.jpg

文档

图书

视频

课程

厂商

图集

链接

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