SqueezeNet（挤压网）
SqueezeNet (2024-02-23, Java, 0KB, 下载0次)
数据骨干网
data backbone (2024-02-11, Java, 0KB, 下载0次)
头脑风暴网，，
BraiNet,, (2019-07-31, Java, 0KB, 下载0次)
为娱乐而编码，脑力训练，
Coding for fun, brain exercises, (2015-12-19, Java, 0KB, 下载0次)
数学大脑娱乐应用程序，
Mathematical Brain Teasing App, (2021-04-13, Java, 0KB, 下载0次)
整蛊专家,娱乐小项目,
Trickster, entertainment project, (2018-02-27, Java, 0KB, 下载0次)
一款简单的android娱乐应用程序，
A simple android app for entertainment, (2020-06-10, Java, 0KB, 下载0次)
神经元othello网，，
neuronal-othello-net,, (2017-11-18, Java, 0KB, 下载0次)
大学网走，，
University-Netwalk,, (2019-02-15, Java, 0KB, 下载0次)
UjiKebolehan7网豆，，
UjiKebolehan7Netbeans,, (2016-11-08, Java, 0KB, 下载0次)
伦敦咖啡网，，
LondonCoffeeWeb,, (2014-11-22, Java, 44KB, 下载0次)
咖啡厅内部网，，
CoffeeShopIntranet,, (2017-05-04, Java, 5756KB, 下载0次)
Deeplink 测试,公网http链接到微信,引导用户默认浏览器打开,然后activity接受传值
Deeplink test, public http link to WeChat, guide the user to open the default browser, and then the activity accepts the value transfer (2020-06-03, Java, 0KB, 下载0次)
Exercícios指的是一份首席执行官名单。
Exercícios referentes a segunda lista de exercício do primeiro estágio. (2016-03-07, Java, 10KB, 下载0次)
微信机器人，一款基于安卓平台的微信机器人。
WechatBot,A wechat robot based on Android platform. (2015-12-19, Java, 28640KB, 下载0次)
wechatbot xposed，一个微信机器人单元，基于android xposed框架钩子实现微信应用程序机器人功能
wechatbot-xposed,A WeChat robot unit ,based on the android xposed framework hook to implement WeChat app robot functions (2018-08-28, Java, 264KB, 下载0次)
微信自动回复，群管理，群聊天，群应用智能机器人
Wechat auto reply, group management, group chat, group application intelligent robot (2020-01-13, Java, 29684KB, 下载8次)
微信开发平台自动聊天机器人java代码，在里面设置下自己的mishi。
Micro-channel automated chat robot development platform java code, in which setting their mishi. (2017-01-09, Java, 1297KB, 下载9次)
ant脚本的环境文件，这是ant脚本2015年目前最新的官网环境文件。
Environment of the ant script file, this is the ant script in 2015 is the latest website environment file. (2015-09-14, Java, 8111KB, 下载3次)
The speed value is obtained at the
multilayer Artificial Neural Network (ANN) output
and the feedback is connected between the output
and the input node so as to extract the dynamic
recurrent neural network features.
The speed value is obtained at the
multilayer Artificial Neural Network (ANN) output
and the feedback is connected between the output
and the input node so as to extract the dynamic
recurrent neural network features.
(2011-03-15, Java, 736KB, 下载10次)