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PFEBOUIDI on Windows Pc

Developed By: BOUIDI Abderrahmane

License: Free

Rating: 5,0/5 - 1 votes

Last Updated: July 03, 2022

Download on Windows PC

Compatible with Windows 10/11 PC & Laptop

App Details

Version 1.0
Size 1 MB
Release Date July 03, 22
Category Education Apps

Description from Developer:
Image Recognition, in the context of Computer Vision, is the ability of software to identify objects, places, people, writings and actions in images. Computers can use machine visi... [read more]

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About this app

On this page you can download PFEBOUIDI and install on Windows PC. PFEBOUIDI is free Education app, developed by BOUIDI Abderrahmane. Latest version of PFEBOUIDI is 1.0, was released on 2022-07-03 (updated on 2022-07-03). Estimated number of the downloads is more than 1. Overall rating of PFEBOUIDI is 5,0. Generally most of the top apps on Android Store have rating of 4+. This app had been rated by 1 users, 1 users had rated it 5*, 1 users had rated it 1*.

How to install PFEBOUIDI on Windows?

Instruction on how to install PFEBOUIDI on Windows 10 Windows 11 PC & Laptop

In this post, I am going to show you how to install PFEBOUIDI on Windows PC by using Android App Player such as BlueStacks, LDPlayer, Nox, KOPlayer, ...

Before you start, you will need to download the APK/XAPK installer file, you can find download button on top of this page. Save it to easy-to-find location.

[Note] You can also download older versions of this app on bottom of this page.

Below you will find a detailed step-by-step guide, but I want to give you a fast overview of how it works. All you need is an emulator that will emulate an Android device on your Windows PC and then you can install applications and use it - you see you're playing it on Android, but this runs not on a smartphone or tablet, it runs on a PC.

If this doesn't work on your PC, or you cannot install, comment here and we will help you!

  1. Install using BlueStacks
  2. Install using NoxPlayer

Step By Step Guide To Install PFEBOUIDI using BlueStacks

  1. Download and Install BlueStacks at: https://www.bluestacks.com. The installation procedure is quite simple. After successful installation, open the Bluestacks emulator. It may take some time to load the Bluestacks app initially. Once it is opened, you should be able to see the Home screen of Bluestacks.
  2. Open the APK/XAPK file: Double-click the APK/XAPK file to launch BlueStacks and install the application. If your APK/XAPK file doesn't automatically open BlueStacks, right-click on it and select Open with... Browse to the BlueStacks. You can also drag-and-drop the APK/XAPK file onto the BlueStacks home screen
  3. Once installed, click "PFEBOUIDI" icon on the home screen to start using, it'll work like a charm :D

[Note 1] For better performance and compatibility, choose BlueStacks 5 Nougat 64-bit read more

[Note 2] about Bluetooth: At the moment, support for Bluetooth is not available on BlueStacks. Hence, apps that require control of Bluetooth may not work on BlueStacks.

How to install PFEBOUIDI on Windows PC using NoxPlayer

  1. Download & Install NoxPlayer at: https://www.bignox.com. The installation is easy to carry out.
  2. Drag the APK/XAPK file to the NoxPlayer interface and drop it to install
  3. The installation process will take place quickly. After successful installation, you can find "PFEBOUIDI" on the home screen of NoxPlayer, just click to open it.

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Download older versions

Other versions available: 1.0.

Download PFEBOUIDI 1.0 on Windows PC – 1 MB

Image Recognition, in the context of Computer Vision, is the ability of software to identify objects, places, people, writings and actions in images. Computers can use machine vision technologies in combination with a camera and artificial intelligence software to achieve image recognition.
Image classification refers to a process in computer vision that can classify an image based on its visual content. For example, an image classification algorithm can be designed to indicate whether or not an image contains a human figure. Although object detection is trivial for humans, robust image classification remains a challenge for computer vision applications.
The objective of this study is to determine what makes a deep neural network processing complex data, such as image/video data, faster and more accurate, we will examine the latest successful neural network architectures to determine what is the most efficient (and fastest) architecture(s) in image classification, and we will also research which optimization techniques work best in this type of data.
We try to understand how researchers recently took a big step forward in visual recognition by classifying images, and see how they scored an incredible accuracy score on the ImageNet challenge. Taking into account how can we process complex data like image data faster, how can we handle the problem of overfitting on this data, and how can we minimize the training time of our architecture.