利用TensorFlow(TF),本作业实现了一个基于full convolution stack、inception v2 module等模块的图片分类网络,纵向共包含10层包含参数的层,采用自己搭建的卷积层。对于dset1与dset2采用同样的网络结构,分别进行训练。最终在dset1验证集(约含900张图,下同)上的Top1分类准确率约为0.52,在dset2验证集上的Top1准确率约为0.63。在K80显卡的单核上,该模型的训练速度约为205张图每秒,最终所得模型的checkpoint约为45MB。
☆12May 14, 2018Updated 8 years ago
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