5 Exciting Computer Vision Applications With Relevant Datasets!

Overview

  • Computer vision is the technology that allows the digital world to interact with the real world.
  • Explore 5 of the hottest applications of Computer Vision

Introduction

I started using Facebook 10 years ago. Likewise, if you used that long ago you must remember the manual tagging of photographs. But now we do not have to tag these pictures manually. Facebook recognizes most of the people in the uploaded picture and provides suggestions to tag them. Similarly, you must have seen those hilarious filters on Snapchat where people use the dog filter and get a dog face on. Have you ever wondered how is all of it possible? How is our phone able to detect our face and add the filters over it? These are some of the computer vision applications.

Image for post

Computer vision is one of the hottest research fields in the data science world. Moreover, it has become a part of our personal lives. Knowingly or unknowingly, we all use various features which have computer vision techniques running at the backend. For instance, we use the face unlock in our smartphones. The image below is efficiently explaining how does face detection works.

Describing face detection technique

I choose face detection for starting this article since this is the one application of computer vision, we all have seen. But trust me computer vision is not limited to this. In this article, you will explore more interesting applications of computer vision.

If you are looking to master in computer vision, check out our course Computer Vision using Deep Learning 2.0

Table of Contents

  • What is Computer Vision?
  • Pose Estimation using Computer Vision
  • Image transformation using Gans
  • Computer Vision for developing Social distancing tools
  • Converting 2D images into 3D models
  • Medical Image analysis

What is Computer Vision?

Before entering into the world of computer vision applications, first, let’s understand what computer vision is? In short, Computer vision is a multidisciplinary branch of artificial intelligence trying to replicate the powerful capabilities of human vision.

If we go through the formal definition,

“Computer vision is a utility that makes useful decisions about real physical objects and scenes based on sensed images” (Sockman & Shapiro, 2001)

Computer vision works through visual recognition techniques like Image classification, object detection, Image segmentation, object tracking, optical character recognition, image captioning, etc. I know these are a lot of technical terms but understanding them is not tough. Just see the image below and you will understand many of these terminologies.

Image for post

Let’s start with the first image. If I ask you what is there in the picture? Your answer will be, its a cat. This is classification. That means labelling the image based on what it consists of is classification. Here the class is ‘Cat’.

Now you know the class of the image. The next question comes where the object is situated in the image. When we identify the location of the object in the frame and create a bounding box around it, It is known as localization. In the second image, we have identified the location of the object and labeled it as a cat.

The next term is the object detection. In the previous two cases, we have a single object in the image but what if there are multiple objects present. Here we identify the instances present and their location via bounding boxes.

In object detection, we use a bounding box that is either square or rectangular in shape but it does not tell anything about the shape of the objects. Instance segmentation creates a pixel-wise mask around each object. Hence instance segmentation gives a deeper understanding of the image.

Check the following resources if you want to know more about Computer Vision-

Recent developments in deep learning approaches and advancements in technology have tremendously increased the capabilities of visual recognition systems. As a result, computer vision has been rapidly adopted by companies. Successful use-cases of computer vision can be seen across the industrial sectors leading to widening the applications and increased demand for computer vision tools.

Now without losing more time, let’s jump into the 5 exciting applications of computer vision.

Human Pose Estimation

Human Pose Estimation is an interesting application of Computer Vision. You must have heard about Posenet, which is an open-source model for Human pose estimation. In brief, pose estimation is a computer vision technique to infer the pose of a person or object present in the image/video.

Before discussing the working of pose estimation let us first understand ‘Human Pose Skeleton’. It is the set of coordinates to define the pose of a person. A pair of coordinates is known as the limb. Further, pose estimation is performed by identifying, locating, and tracking the key points of Humans pose skeleton in an Image or video.

#pose-estimation #computer-vision #gans #applications-of-ai #deep-learning #deep learning

What is GEEK

Buddha Community

5 Exciting Computer Vision Applications With Relevant Datasets!

5 Exciting Computer Vision Applications With Relevant Datasets!

Overview

  • Computer vision is the technology that allows the digital world to interact with the real world.
  • Explore 5 of the hottest applications of Computer Vision

Introduction

I started using Facebook 10 years ago. Likewise, if you used that long ago you must remember the manual tagging of photographs. But now we do not have to tag these pictures manually. Facebook recognizes most of the people in the uploaded picture and provides suggestions to tag them. Similarly, you must have seen those hilarious filters on Snapchat where people use the dog filter and get a dog face on. Have you ever wondered how is all of it possible? How is our phone able to detect our face and add the filters over it? These are some of the computer vision applications.

Image for post

Computer vision is one of the hottest research fields in the data science world. Moreover, it has become a part of our personal lives. Knowingly or unknowingly, we all use various features which have computer vision techniques running at the backend. For instance, we use the face unlock in our smartphones. The image below is efficiently explaining how does face detection works.

Describing face detection technique

I choose face detection for starting this article since this is the one application of computer vision, we all have seen. But trust me computer vision is not limited to this. In this article, you will explore more interesting applications of computer vision.

If you are looking to master in computer vision, check out our course Computer Vision using Deep Learning 2.0

Table of Contents

  • What is Computer Vision?
  • Pose Estimation using Computer Vision
  • Image transformation using Gans
  • Computer Vision for developing Social distancing tools
  • Converting 2D images into 3D models
  • Medical Image analysis

What is Computer Vision?

Before entering into the world of computer vision applications, first, let’s understand what computer vision is? In short, Computer vision is a multidisciplinary branch of artificial intelligence trying to replicate the powerful capabilities of human vision.

If we go through the formal definition,

“Computer vision is a utility that makes useful decisions about real physical objects and scenes based on sensed images” (Sockman & Shapiro, 2001)

Computer vision works through visual recognition techniques like Image classification, object detection, Image segmentation, object tracking, optical character recognition, image captioning, etc. I know these are a lot of technical terms but understanding them is not tough. Just see the image below and you will understand many of these terminologies.

Image for post

Let’s start with the first image. If I ask you what is there in the picture? Your answer will be, its a cat. This is classification. That means labelling the image based on what it consists of is classification. Here the class is ‘Cat’.

Now you know the class of the image. The next question comes where the object is situated in the image. When we identify the location of the object in the frame and create a bounding box around it, It is known as localization. In the second image, we have identified the location of the object and labeled it as a cat.

The next term is the object detection. In the previous two cases, we have a single object in the image but what if there are multiple objects present. Here we identify the instances present and their location via bounding boxes.

In object detection, we use a bounding box that is either square or rectangular in shape but it does not tell anything about the shape of the objects. Instance segmentation creates a pixel-wise mask around each object. Hence instance segmentation gives a deeper understanding of the image.

Check the following resources if you want to know more about Computer Vision-

Recent developments in deep learning approaches and advancements in technology have tremendously increased the capabilities of visual recognition systems. As a result, computer vision has been rapidly adopted by companies. Successful use-cases of computer vision can be seen across the industrial sectors leading to widening the applications and increased demand for computer vision tools.

Now without losing more time, let’s jump into the 5 exciting applications of computer vision.

Human Pose Estimation

Human Pose Estimation is an interesting application of Computer Vision. You must have heard about Posenet, which is an open-source model for Human pose estimation. In brief, pose estimation is a computer vision technique to infer the pose of a person or object present in the image/video.

Before discussing the working of pose estimation let us first understand ‘Human Pose Skeleton’. It is the set of coordinates to define the pose of a person. A pair of coordinates is known as the limb. Further, pose estimation is performed by identifying, locating, and tracking the key points of Humans pose skeleton in an Image or video.

#pose-estimation #computer-vision #gans #applications-of-ai #deep-learning #deep learning

Inside ABCD, A Dataset To Build In-Depth Task-Oriented Dialogue Systems

According to a recent study, call centre agents’ spend approximately 82 percent of their total time looking at step-by-step guides, customer data, and knowledge base articles.

Traditionally, dialogue state tracking (DST) has served as a way to determine what a caller wants at a given point in a conversation. Unfortunately, these aspects are not accounted for in popular DST benchmarks. DST is the core part of a spoken dialogue system. It estimates the beliefs of possible user’s goals at every dialogue turn.

To reduce the burden on call centre agents and improve the SOTA of task-oriented dialogue systems, AI-powered customer service company ASAPP recently launched an action-based conversations dataset (ABCD). The dataset is designed to help develop task-oriented dialogue systems for customer service applications. ABCD consists of a fully labelled dataset with over 10,000 human dialogues containing 55 distinct user intents requiring sequences of actions constrained by company policies to accomplish tasks.

https://twitter.com/asapp/status/1397928363923177472

The dataset is currently available on GitHub.

#developers corner #asapp abcd dataset #asapp new dataset #build enterprise chatbot #chatbot datasets latest #customer support datasets #customer support model training #dataset for chatbots #dataset for customer datasets

Joseph  Murray

Joseph Murray

1623302550

Top 5 Java Web Application Technologies You Should Master in 2021

Web Development in Java

Java is a commonly used language for web development, especially on the server-side. Java web applications are distributed applications that run on the internet. Web development with Java allows us to create dynamic web pages where users can interact with the interface.

There are various ways through which you can create dynamic web pages in Java. The Java EE (Enterprise Edition) platform provides various Java technologies for web development to developers. Services like distributed computing, web services, etc. are provided by Java EE. Applications can be developed in Java without using any additional scripting language. Let us see how web applications are made via Java.

**Java Web Application **

Java Web Application Technologies

#software development #java #java web applications #web applications #java web application technologies #top 5 java web application technologies you should master

How Dataset size or RAM chokes your Deep Learning for Computer Vision

a simple way to protect your computer RAM from overloading and promise your DNN training’s success on a huge image dataset.

Image for post

photo by author

Background

Dealing with large image datasets, computer memory can be easily overloaded. Some people don’t have an idea about how large an image dataset could be. The MNIST dataset, although each handwritten digit is in 28x28, is composed of a training set of 60,000 examples, and a test set of 10,000 examples. It doesn’t require too much hard drive capacity for the downloaded dataset. But when we read the dataset into Numpy array, too much memory (RAM) will be taken. Instead of an array output, an error message “run out of memory” appears on the screen. What is worse, with the development of Data Science, the size of datasets for our researches is growing up. The COCO dataset, the Cityscapes dataset, etc. need much larger both hard drive capacity and memory.

It seems that we have to buy better and more expensive equipment to struggle with limited computer memory. Otherwise, we can’t proceed these huge image datasets.

Image for post

Machine Learning Jobs

On the other hand, deep learning algorithms require a great many computer calculations, which could also run out of computer memory. The classification, detection, segmentation algorithms of Computer Vision with DNN handle with enormous data volume. The more train data, the better our result. Though we have access to big datasets, like Pascal VOC, COCO, Cityscapes, which are often and free for everyone. Our poor RAM doesn’t allow our processing of huge data. Either the dataset size or RAM chokes my deep learning like a force choke👹.

Image for post

#dataset #computer-vision #python #deep-learning #ai

Ethen Ellen

1619519725

Immediate $olution to Fix AOL Blerk Error Code 5 with easy instructions

This is image title

AOL Email is one of the leading web email services. It has a number of features who access easily at any place. Through this, you can easily share messages, documents or files, etc.AOL Blerk Error is not a big issue. It is a temporary error and it occurs when there is an issue in loading messages from the AOL server. If your mind is stuck, How to Resolve or Fix AOL Blerk Error Code 5? Here, In this article, we mentioned troubleshooting steps to fix AOL Blerk Error Code 5.

What are the causes of AOL Blerk Error Code 5?

AOL mail usually presents an AOL Blerk Error 5 after the AOL connection details have been entered. meaning. Your password and your username. This error is usually found in words! Or 'BLERK! Error 5 Authentication problem, 'Your sign-in has been received.

Some of the reasons for the error are as follows:
• Internet browser configuration problem

• Saved erroneous bookmark addresses

• browser cache or cookie

• An AOL Desktop Gold technical error.
How to Fix AOL Mail Blerk Error 5 in a Simple Way

This type of error is mostly due to your browser settings or the use of outdated, obsolete software. Users should remember that the steps to solve problems vary, depending on the browser you are using. Here are the steps to fix the mistake, check your browser and follow the steps.

Internet Explorer: Make sure you use the most recent web browser version. Open a new window and follow the “Tools> Web Options> Security> Internet Zone” thread. Activate ‘Safeguard Mode’ and follow the steps to include AOL Mail in the list of assured websites. Start the browser again to save changes and run Internet Explorer without additional information.
Firefox Mozilla: Open a new Firefox window and press Menu. To start the browser in safe mode, disable the add-on and choose the option to restart Firefox. You can see two options in the dialog box. Use the “Start in Safe Mode” option to disable all themes and extensions. The browser also turns off the hardware speed and resets the toolbar. You should be able to execute AOL mail when this happens.

Google Chrome: Update to the latest version of Chrome. Open the browser and go to the Advanced Options section. Go to ‘Security and Privacy’ and close the appropriate add-ons. Once the browsing history is deleted, the password, cookies saved and the cache will be cleared. Restart your system and try to log in to your AOL account with a new window.

Safari: Some pop-up windows block AOL mail when it comes to Safari and causes authentication issues. To fix the error, use Safari Security Preferences to enable the pop-up window and disable the security warning.

If you see, even when you change the required browser settings, the black error will not disappear, you can consult a skilled professional and see all the AOL email customer support numbers.

Get Connect to Fix Blerk Error Even After Clearing Cache & Cookies?
Somehow you can contact AOL technical support directly and get immediate help if you still get the error. Call +1(888)857-5157 to receive assistance from the AOL technical support team.

Source: https://email-expert247.blogspot.com/2021/04/immediate-olution-to-fix-aol-blerk.html “How to Resolve or Fix AOL Blerk Error Code 5”)**? Here, In this article, we mentioned troubleshooting steps to fix AOL Blerk Error Code 5.

What are the causes of AOL Blerk Error Code 5?

AOL mail usually presents an AOL Blerk Error 5 after the AOL connection details have been entered. meaning. Your password and your username. This error is usually found in words! Or 'BLERK! Error 5 Authentication problem, 'Your sign-in has been received.

Some of the reasons for the error are as follows:
• Internet browser configuration problem

• Saved erroneous bookmark addresses

• browser cache or cookie

• An AOL Desktop Gold technical error.
How to Fix AOL Mail Blerk Error 5 in a Simple Way

This type of error is mostly due to your browser settings or the use of outdated, obsolete software. Users should remember that the steps to solve problems vary, depending on the browser you are using. Here are the steps to fix the mistake, check your browser and follow the steps.

  1. Internet Explorer: Make sure you use the most recent web browser version. Open a new window and follow the “Tools> Web Options> Security> Internet Zone” thread. Activate ‘Safeguard Mode’ and follow the steps to include AOL Mail in the list of assured websites. Start the browser again to save changes and run Internet Explorer without additional information.

  2. Firefox Mozilla: Open a new Firefox window and press Menu. To start the browser in safe mode, disable the add-on and choose the option to restart Firefox. You can see two options in the dialog box. Use the “Start in Safe Mode” option to disable all themes and extensions. The browser also turns off the hardware speed and resets the toolbar. You should be able to execute AOL mail when this happens.

  3. Google Chrome: Update to the latest version of Chrome. Open the browser and go to the Advanced Options section. Go to ‘Security and Privacy’ and close the appropriate add-ons. Once the browsing history is deleted, the password, cookies saved and the cache will be cleared. Restart your system and try to log in to your AOL account with a new window.

  4. Safari: Some pop-up windows block AOL mail when it comes to Safari and causes authentication issues. To fix the error, use Safari Security Preferences to enable the pop-up window and disable the security warning.

If you see, even when you change the required browser settings, the black error will not disappear, you can consult a skilled professional and see all the AOL email customer support numbers.

Get Connect to Fix Blerk Error Even After Clearing Cache & Cookies?

Somehow you can contact AOL technical support directly and get immediate help if you still get the error. Call +1(888)857-5157 to receive assistance from the AOL technical support team.

Source: https://email-expert247.blogspot.com/2021/04/immediate-olution-to-fix-aol-blerk.html

#aol blerk error code 5 #aol blerk error 5 #aol mail blerk error code 5 #aol mail blerk error 5 #aol error code 5 #aol error 5