1. 毕业设计（论文）主要目标：
1、阅读机器学习领域相关文献，特别是近年来的深度网络学习方面的经典文献2、以VGGNet为基础，熟悉深度卷积网络模型的基本原理及其实现3、开发基于深度卷积网络的人体属性检测与分割原型系统
2. 毕业设计（论文）主要内容：
该行人属性检测系统主要基于深度卷积神经网的基本思想，采用深度卷积神经网络的基本框架应用在服装部位与人体部位的检测。经过大量数据对模型进行训练，能够对图像中的行人头部、上身、下身、脚、帽子、包位置进行标注。
3. 主要参考文献
[1] Viola P, Jones M.Rapid object detection using a boosted cascade of simple features[C]//Proceeding of CVPR2001 ,Kauai,HI,USA,2001:511-518.[2] Pan R,Gao W, Liu J,et al.Automatic recognition of woven fabric pattern based on image processing and BP neural network[J].The Journal of the Textile Institute,2011,102(1):19-30. [3] Salem Y B,Nasri S.Automatic recognition of woven fabrics bassed on texture and using SVM[J].Signal,image and video processing,2010,4(4):429-434.[4] Yang H F,Lin K,Chen C S.Supervised Learning of Semantics-Preserving Hashing via Deep Neural Networks for Large-Scale Image Search[J].arXiv preprint arXiv:1507.00101,2015.[5] M.D.Zeiler and R.Fergus.Visualizing and understanding convolutional neural networks.In ECCV,2014.[6] Liu S,Feng J,Domokos C,et al.Fashion parsing with weak color-cateory lables[J].Multimedia,IEEE Transactions on,2014,16(1):253-265.[7] Hu Z,Yan H,Lin X.Clothing segmentation using foreground and background estimation based on the constrained Delaunay triangulation[J].Pattern Recognition,2008,41(5):1581-1592.[8] Weber M,Bauml M,Atiefelhagen R.Part-based clothing segmentation for person retrieval[C]//Advance Video and Dignal-Based Surveillance (AVSS),2011 8th IEEE International Conference on.IEEE,2011:361-366.
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