QA Official

machine learning-cross validation in ——sklearn

https://qaofficial.com/post/2019/05/15/70233-machine-learning-cross-validation-in-sklearn.html 2019-05-15
reprinted from http://blog.csdn.net/jasonding1354/article/details/50562513. Content Summary Disadvantages of Training Set/Test Set Segmentation for Model Verification K Fold Cross Verification How to Overcome Previous DeficienciesHow can cross-validation be used to select adjustment parameters, select models, and select featuresImproved Cross Validation

of Java operator

https://qaofficial.com/post/2019/05/15/70077-of-java-operator.html 2019-05-15
autoaddition is a single-purpose operator divided into: pre ++(a++), and post ++(++a), which is usually used in assignment statements. a++: assign a value before performing a=a+1 ++a: perform a=a+1 before assigning Example 1: int a=1; int b=a++; a=1; int c=++a; System.out.println("b="+b+",c="+c); Results: b=1,c=2 Example 2: int i=1; i=i++; int j=1; j=++j; System.out.println("i="+i+",j="+j); Results: i=1,j=2 Analysis: i=i++ Store the old value of I in temp and then let I add it by itself.

paper reading: look-ahead before you leave: end-to-end active

https://qaofficial.com/post/2019/05/15/70708-paper-reading-look-ahead-before-you-leave-end-to-end-active.html 2019-05-15
1. Problems Solved in the Paper 2. What is Active Vision 3. Differences from visual saliency, visual attention (visual saliency and attention) and prediction related features (equivalent to differences between this article and previous methods) 4. Solution of the thesis 5. To what extent has the solution in the paper solved this problem? 6. Other Issues Not Considered 7. Experiments

sufficiency of training data (1): PAC learning guarantee

https://qaofficial.com/post/2019/05/15/70374-sufficiency-of-training-data-1-pac-learning-guarantee.html 2019-05-15
Training errors and actual errors were introduced in the previous blog post.When the training errors are very low, but the actual errors are very high, it shows that the classifier we constructed has over-fitting.The reason for over-fitting is that the classifier we designed is too complex to record all the classification data.This leads to poor scalability of the classification model.Therefore, the complexity of classifier is closely related to the scale of training data.

Android Face Recognition-Summary on the Use of Hongruan Face Recognition SDK Engine

https://qaofficial.com/post/2019/05/13/71805-android-face-recognition-summary-on-the-use-of-hongruan-face-recognition-sdk-engine.html 2019-05-13
Hong Ruan recently opened the SDK engine for face recognition (free of charge), which happened to have Android version and experienced a wave.Let's talk about Android SDK usage experience: ArcFace Hongruan Face Recognition Engine The currently open versions of human face comparison (1:1) and face retrieval (1: N) can be selected according to the application scenario. Face Retrieval is divided into small network (within 100 persons), medium network (within 1000

Android Owns Face Detection API Analysis

https://qaofficial.com/post/2019/05/13/71820-android-owns-face-detection-api-analysis.html 2019-05-13
Use FaceDetectionListener进行人脸检测 package com.emptech.biocollection.fragment; import android.Manifest; import android.content.pm.PackageManager; import android.graphics.ImageFormat; import android.graphics.Point; import android.hardware.Camera; import android.os.Bundle; import android.support.annotation.NonNull; import android.support.annotation.Nullable; import android.support.v4.content.ContextCompat; import android.util.Log; import android.view.LayoutInflater; import android.view.SurfaceHolder; import android.view.SurfaceView; import android.view.View; import android.view.ViewGroup; import android.widget.ImageView; import android.widget.Toast; import com.emptech.biocollection.R; import com.emptech.biocollection.socket.MessageType; import com.emptech.biocollection.socket.message.IPreview;

Android Understand Simple Native FaceDetector Face Recognition in One Minute, Solve Unclear Video Recorded by SurfaceView+MediaRecorder

https://qaofficial.com/post/2019/05/13/71817-android-understand-simple-native-facedetector-face-recognition-in-one-minute-solve-unclear-video-recorded-by-surfaceview-mediarecorder.html 2019-05-13
Recently, I found that I logged into the background management system and found that the authentication video uploaded was too vague. As a result, I found that I did not set the frame frequency for MediaRecorder. // 设置帧频率,录制视频会更加清晰 mRecorder.setVideoEncodingBitRate(5*1024*1024); 1. Open the camera directly to get the desired bitmap. About why YUV Image: https://blog.csdn.net/illidantao/article/details/51366047 is used

Android gets the picture through the network URL and displays it

https://qaofficial.com/post/2019/05/13/71794-android-gets-the-picture-through-the-network-url-and-displays-it.html 2019-05-13
1. Layout file <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android" xmlns:tools="http://schemas.android.com/tools" android:layout_width="match_parent" android:layout_height="match_parent" tools:context="${relativePackage}.${activityClass}" android:orientation="vertical" > <TextView android:layout_width="wrap_content" android:layout_height="wrap_content" android:text="@string/hello_world" /> <ImageView android:id="@+id/imageView" android:layout_width="wrap_content" android:layout_height="wrap_content"/> <Button android:id="@+id/button" android:layout_width="300dp" android:layout_height="70dp" android:layout_gravity="center_horizontal" android:text="获取网络图片"/> </LinearLayout&g

EmguCV configuration considerations

https://qaofficial.com/post/2019/05/13/71842-emgucv-configuration-considerations.html 2019-05-13
本文介绍了EmguCV3.1.0与VisualStudio2013配置注意事项。 本文使用的操作系统为win7、64位。 1.前言 EmguCV库

OPENCV Eye Detection

https://qaofficial.com/post/2019/05/13/71782-opencv-eye-detection.html 2019-05-13
本篇博客主要是对前段时间数字图像课程大作业-疲劳检测所做工作的一次总结整理。主要涉及到的内容有1、基于图片的人脸、人眼检测;2、利用OPEN