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Practical examples of deep learning | Explain what you can do and services!

Table of Contents 

  • What is deep learning
  • Why is deep learning attracting attention?
  • 4 Things Deep Learning Can Do
    • image recognition
    • voice recognition
    • natural language processing
    • Anomaly detection
  • [By Field] 8 Practical Examples of Deep Learning
    • Autonomous Driving | Advanced Driving Automation
    • Aviation|Immigration/Defense
    • Manufacturing/Production|Automation/Safety Management
    • Mail order|Image search technology
    • EC site|Recommendation function
    • Economy | Stock market forecast
    • Security|Surveillance cameras and unauthorized access prevention
    • Warehouse|Inventory management, etc.
  • 8 products and services that utilize deep learning
    • Deep L
    • Petalica Paint
    • Deep Gram
    • Otter.ai
    • Deep Nostalgia
    • Grid Space
    • Cloud Speech-to-Text
    • Amazon Echo
  • How deep learning will be used in the future
  • summary

What is deep learning

Deep learning is one of machine learning, and it is a technology that a computer automatically analyzes a large amount of data and extracts the characteristics of the data. It is also known as deep learning or DL ​​for short.

Deep learning gets its name from the multiple intermediate layers of a neural network (NN) in its structure.

By adding multiple intermediate layers, it is possible to learn the characteristics of the data more deeply.

Why is deep learning attracting attention?

One of the reasons deep learning is attracting attention is its high accuracy. Especially in fields such as image authentication, both speed and accuracy are extremely high.

Behind this rapid evolution is the improvement in server processing power. The increased processing power of servers has made it possible to process large amounts of data.

4 Things Deep Learning Can Do

What deep learning can do can be divided into four main areas: image recognition, voice recognition , natural language processing , and anomaly detection. I will explain each one.

image recognition

Image recognition is one of the pattern recognition technologies for identifying objects by capturing features from images.

By giving the computer a large number of images from the database and having the computer automatically learn the features of the object, the computer will be able to recognize the object.

voice recognition

Speech recognition is a technology that converts voice data into text data on a computer.

Computers analyze and recognize speech using acoustic models and language models. Deep learning has made it possible to automatically predict words that are likely to appear next.

natural language processing

A natural language is a human-made language such as Japanese or English. On the other hand, strictly defined languages ​​like programming languages ​​are called formal languages.

Natural language processing is a technology that extracts content by processing human words with a machine. By using deep learning, it is possible to analyze the difference in meaning of languages ​​with the same pronunciation.

Anomaly detection

Anomaly detection using deep learning is a technology for detecting and identifying data that differs from other data in a dataset.

It can capture subtle changes that humans cannot perceive, as well as minute movements of machines before they break down.

[By Field] 8 Practical Examples of Deep Learning

In this chapter, we introduce eight specific practical examples of deep learning.

  1. Autonomous Driving | Advanced Driving Automation
  2. Aviation|Immigration/Defense
  3. Manufacturing/Production|Automation/Safety Management
  4. Mail order|Image search technology
  5. EC site|Recommendation function
  6. Economy | Stock market forecast
  7. Security|Surveillance cameras and unauthorized access prevention
  8. Warehouse|Inventory management, etc.

I will explain each.

Autonomous Driving | Advanced Driving Automation

Currently, in Japan, various companies, including Toyota and Honda, are conducting demonstration tests of advanced driving automation and developing safe driving support systems.

Driving a car requires not only speed and direction control, but also many judgment and recognition abilities such as whether there are any obstacles in front, whether there are passers-by, what the color of the traffic light is, and what direction the destination is. is asked.

Therefore, very delicate technology is required. By using deep learning to learn from a huge amount of past driving data and image data, it has achieved decision-making power similar to that of humans.

Aviation|Immigration/Defense

The Immigration Bureau of the Ministry of Justice has introduced face recognition gates to simplify immigration procedures for Japanese returnees.

Your identity will be verified by comparing the photo of your face on the IC chip in your passport with the photo of yourself taken at the immigration gate. Proprietary technology can also recognize facial changes due to aging, makeup, and facial expressions.

In addition, by analyzing images obtained from artificial satellites using deep learning techniques, it is possible to recognize and detect objects on the ground, and it is also used for national border defense.

Manufacturing/Production|Automation/Safety Management

In addition to automating the production line, deep learning also automates the management of the production site, making it possible to manufacture products completely unmanned.

All operations can be automated, such as factory temperature control, product inspection, and adjustment of robots for quality improvement.

In addition, a function that automatically detects when a person or object enters the vicinity of a moving heavy machinery and stops the operation safely has been put to practical use.

Mail order|Image search technology

A service that uses deep learning to upload a photo of the product you want and find similar products from the huge number of products posted on the site.

This technology is also applied to image searches on shopping sites.

EC site|Recommendation function

An e-commerce site is a website that sells products on the Internet.

Many of you probably use Mercari or Amazon. The recommendation function is an easy-to-understand application of deep learning on an EC site.

By analyzing the user’s preferences based on their browsing history and click behavior on the site, we have realized recommendations that are in high demand by users.

Economy | Stock market forecast

In recent years, AI has also been used in the field of economics.

Using deep learning, it is possible to predict future fluctuations in stock prices based on past data and trading behavior based on various laws, and achieve high yields.

Security|Surveillance cameras and unauthorized access prevention

Deep learning is also used in surveillance cameras, such as automatically reporting to administrators or the police when a suspicious person or suspicious movement is detected by the camera. Cybercrime such as unauthorized access can also be prevented.

In addition, by constantly monitoring the internal system with AI, when suspicious access or logs are detected, it is possible to quickly move to troubleshooting. This helps prevent cybercrime such as unauthorized access.

Warehouse|Inventory management, etc.

By introducing image recognition AI to warehouse operations, it becomes possible to streamline and automate operations such as inventory management. Deep learning is also being put into practical use for picking work and sorting of deliveries.

8 products and services that utilize deep learning

Here, we introduce eight recommended products and services that utilize deep learning.

  1. Deep L
  2. Petalica Paint
  3. Deep Gram
  4. Otter.ai
  5. Deep Nostalgia
  6. Grid Space
  7. Cloud Speech-to-Text
  8. Amazon Echo

Deep L

DeepL is a service that automatically translates sentences. Now, I think most people have used a foreign language automatic translation tool. DeepL has a reputation for being more natural than Google Translate.

Petalica Paint

Petalica Paint is a service that automatically colors the pictures you draw. Coloring is a very difficult and time-consuming task, so if you can master it, you will be able to draw more of your favorite pictures.

Deep Gram

DeepGram is a service that recognizes the audio contained in uploaded videos, allowing them to be searched and organized.

Otter.ai

Otter.ai is a cloud-based automatic transcription tool that turns spoken words into text. Currently, it only supports English, but it is used for coverage of overseas exhibitions.

Deep Nostalgia

Deep Nostalgia is a service that allows you to move faces in photos using deep learning technology.

The service can even move faces in old photos, making the deceased feel as if they were alive.

Grid Space

GridSpace is a meeting support device that records and summarizes the content of meetings.

It also automatically records who said what in the meeting, indexes those sentences, and even highlights what you think is important in the meeting.

Cloud Speech-to-Text

Cloud Speech-to-Text is a service that AI recognizes and converts audio files in “Google Cloud Platform” provided by Google as a cloud service.

Amazon Echo


Amazon Echo is a type of smart speaker, and there are various types ranging from about 5,000 yen to over 20,000 yen .

It is a popular product because it has many functions such as music playback and schedule management, all of which can be operated by voice.

How deep learning will be used in the future

Deep learning can be used in a variety of ways, and services for various industries such as medicine and manufacturing have already been developed. progressing.

Since it can be used in a wide range of ways, from free services for individuals to advanced systems for companies, deep learning will continue to be used in a wider variety of fields.

Summary

In this article, we have introduced practical examples of deep learning. I think you now understand that deep learning is being used in a variety of fields.

Some of the services introduced this time can be easily used by individuals, so please try using them.

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