使用了两个卷积层.一个全连接层和一个softmax分类器. 在测试数据集上正确率可以达到99.22%. 代码参考了neural-networks-and-deep-learning #coding:utf8 import cPickle import numpy as np import theano import theano.tensor as T from theano.tensor.nnet import conv from theano.tensor.nnet import softm
Mode Decision(模式选择)决定一个宏块以何种类型进行分割.宏块的分割类型有以下几种: //P_Skip and B_Skip means that nothing need to be encoded for this macroblock , // just use the mv predicted to restruct the macroblock //B_Direct means use no mvd and no refidx, // just use the mv abt
mysql 演示数据库:http://downloads.mysql.com/docs/sakila-db.zip 以%开头的LIKE查询不能够利用B-tree索引 explain select * from actor where last_name like '%NI%'\G; explain select * from actor where last_name like 'NI%'\G; 解决办法 先扫描索引 last_name获取满足条件的%NI%的主键actor_id列表,之后根据主