SQUEEZENET: ALEXNET-LEVEL ACCURACY WITH 50X FEWER PARAMETERS AND <0.5MB MODEL SIZE

- Fire modules consisting of a 'squeeze' layer with 1*1 filters feeding an 'expand' layer with 1*1 and 3*3 filters(通過餵食一個包含1*1和3*3濾波器的'擴展'層,激勵包含一個'擠壓'層的模塊) - AlexNet level accuracy on ImageNet with 50x fewer parameters(具有AlexNet水平的精度,卻少了50倍的參數量) - Ca

Google : Op-Amp Level Shifter Level shifting a +/- 2.5V signal to 0 - 5V I have a front end module that generates an (ECG) signal that varies from +/-2.5 V. I want to shift this signal to 0 - 5V. What is the best way to do this? First thing to try is

org.mybatis.spring.MyBatisSystemException: nested exception is org.apache.ibatis.binding.BindingException: Parameter 'offset' not found. Available parameters are [0, 1, param1, param2] at org.mybatis.spring.MyBatisExceptionTranslator.translateExcepti

转自:https://blog.csdn.net/wdehxiang/article/details/77619569 原因: 传入多个值时,mybatis会自动将这些值转成类似map形式的值,以0,1,2…的序列为keyName. 这里我们需要先简单了解一下mybatis的传值机制.Mybatis现在可以使用的parameterType有基本类型和Java负责类型 基本数据类型:包含int,String,Date等.基本数据类型作为传参,只能传入一个.通过#{参数名}获取. 复杂数据类型:包含

eclipse在dao层写的模糊查询sql:String sql = "select count(*) from product where pname like '%?%'": 这样写会导致以下错误 Wrong number of parameters: expected 0, was given 1 Query: select count(*) from product where pname like '%?%' Parameters: [%小%]<br/> 原因:

 MyEclipse只是Eclipse的一个插件,所以MyEclipse本身不带JDK,JDK是你事先装好并且配置Environment Variable完成后的.Eclipse自动配置完成的.当然Eclipse环境里似乎有一个编译器.在Window--Preferences--Java--Compiler下面选择 你是不是这里选择了6.0了?把它改成与你当前版本相同的版本.或是低级版本. 不用理会,JDK6.0向下支持J2EE1.4,放心大胆的用,只要Application Server不

转自:https://github.com/ritchieng/the-incredible-pytorch The Incredible PyTorch What is this? This is inspired by the famous Awesome TensorFlow repository where this repository would hold tutorials, projects, libraries, videos, papers, books and anythi

Review: LeNet-5 1998 by LeCun, one conv layer. Case Study: AlexNet [Krizhevsky et al. 2012] It uses a lot of mordern techniques where is still limited to historical issues (seperated feature maps, norm layers). Kind of obsolete, but it is the first C

選自GitHub 作者:Simon Brugman 參與:吳攀 深度學習已經在語音識別.機器翻譯.圖像目標檢測和聊天機器人等許多領域百花齊放.近日,GitHub 用戶 Simon Brugman 發布了一個按任務分類的深度學習論文項目,其按照不同的任務類型列出了一些當前最佳的論文和對起步有用的論文. 目錄 1. 文本 1.1. 代碼生成(Code Generation) 1.2. 情感分析(Sentiment Analysis) 1.3. 翻譯(Translation) 1.4. 分類(Clas