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README.md

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+# ILGnet
+
+This is an open-source project for the aesthetic evaluation of images based on the deep learning-caffe framework, which we completed in our BestiVictory team lab.
+The Internet
+
+The Deep Convolutional Neural Network (DCNN) method has recently yielded the desired image aesthetic assessment results. At present, a powerful model is presented, which shows very high performance in binary classification. We propose a new DCNN structure, which is named ILGNet, for image aesthetics classification, the concept of inception introduction ,the middle part of the local layer to connect to the global level for output. In addition, we used CNN to trained the image classification with ImageNet dat...(line truncated)...
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+The way of test
+please use caffe test tools to test accuracy.
+
+The Accuracy 
+We set the dataset about AVA1 and AVA2.The AVA1'accuracy is 81.68%,and the AVA2 accuracy is 85.50%.
+If you find our model/method/dataset useful, please cite our work:
+
+*************************************************************************************
+@inproceedings{DBLP:conf/wcsp/JinCPTYL16,
+  author    = {Xin Jin and
+               Jingying Chi and
+               Siwei Peng and
+               Yulu Tian and
+               Chaochen Ye and
+               Xiaodong Li},
+  title     = {Deep image aesthetics classification using inception modules and fine-tuning
+               connected layer},
+  booktitle = {8th International Conference on Wireless Communications {\&} Signal
+               Processing, {WCSP} 2016, Yangzhou, China, October 13-15, 2016},
+  pages     = {1--6},
+  year      = {2016},
+  crossref  = {DBLP:conf/wcsp/2016},
+  url       = {http://dx.doi.org/10.1109/WCSP.2016.7752571},
+  doi       = {10.1109/WCSP.2016.7752571},
+  timestamp = {Fri, 16 Dec 2016 12:48:17 +0100},
+  biburl    = {http://dblp.uni-trier.de/rec/bib/conf/wcsp/JinCPTYL16},
+  bibsource = {dblp computer science bibliography, http://dblp.org}
+}
+***************************************************************************************
+
+
+Latest edit
+Jan 15, 2017
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