Saturday, March 6, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Data Science

Machine Learning on Mobile: An On-device Inference App for Skin Cancer Detection

August 19, 2019
in Data Science
Machine Learning on Mobile: An On-device Inference App for Skin Cancer Detection
605
SHARES
3.4k
VIEWS
Share on FacebookShare on Twitter

Mobile health (mHealth) is considered one of the most transformative drivers for health informatics delivery of ubiquitous medical applications. Machine learning has proven to be a powerful tool in classifying medical images for detecting various diseases. However, supervised machine learning requires a large amount of data to train the model, whose storage and processing pose considerable system requirements challenges for mobile applications. Therefore, many studies focus on deploying cloud-based machine learning, which takes advantage of the Internet connection to outsource data-intensive computing.

However, this kind of approach comes with certain drawbacks:

You might also like

A Plethora of Machine Learning Articles: Part 2

The Effect IoT Has Had on Software Testing

Why Cloud Data Discovery Matters for Your Business

▸Latency: It takes time for a cloud-based service to respond to a client request.

▸Privacy: Privacy issues might arise by sending sensitive data to the cloud, especially in the context of medical and health applications.

▸Cost: Cloud-based approaches incur financial costs from cloud service providers.

▸Connectivity: a Network connection is essential to run the cloud-based app, but cloud-based service may not always be available.

▸Customization: In general, cloud services provide generic models based on their common datasets. These models may not be appropriate or customizable for specific health problems.

To tackle these challenges of mHealth applications, we present an on-device inference App. 

On-device Inference for Skin Cancer Detection

We solved this problem by performing the training phase on a powerful computer and the inference phase on a mobile device. the classification model is pre-trained and stored on a mobile device, where it is used to perform classification of new data, which, consequently, does not need to be shared externally. the model is then deployed on a mobile device, where the inference process takes place, i.e. when presented with new test image all computations are executed locally where the test data remains

The architecture of CNNs for Skin Cancer Detection

The convolution and pooling layers perform feature extraction by capturing the general characteristics of the images. The fully connected layers assign a probability for the input image according to the given features.

Data Augmentation

One of the difficulties of automatically processing skin images is that an image may be taken under a variety of conditions (e.g., brightness, angle, focal distance), which makes the comparison of images and identification of pertinent features difficult. To minimize the impact of image parameters on the classification model, we incorporated data augmentation, which in our case produces new images by randomly rotating, zooming, shifting, and cropping from the center of existing images. These additional images can then be used to boost training.

Model Conversion and Integrating Pre-trained Model into the App

this on-device inference approach substantially reduces latency. it improves privacy because it does not require a patient to send images to a third-party cloud service. it eliminates the overhead and cost of running and maintaining cloud services. 

The main limitation of our approach is that the pre-trained model is not easily updated because the offline model is integrated in the app.

Download original pdf from IEEE.


Credit: Data Science Central By: AI

Previous Post

Apex Legends Devs Lash Out at Player. That's Flipping Great

Next Post

Relying on bug bounties 'not appropriate risk management': Katie Moussouris

Related Posts

A Plethora of Machine Learning Articles: Part 2
Data Science

A Plethora of Machine Learning Articles: Part 2

March 4, 2021
The Effect IoT Has Had on Software Testing
Data Science

The Effect IoT Has Had on Software Testing

March 3, 2021
Why Cloud Data Discovery Matters for Your Business
Data Science

Why Cloud Data Discovery Matters for Your Business

March 2, 2021
DSC Weekly Digest 01 March 2021
Data Science

DSC Weekly Digest 01 March 2021

March 2, 2021
Companies in the Global Data Science Platforms Resorting to Product Innovation to Stay Ahead in the Game
Data Science

Companies in the Global Data Science Platforms Resorting to Product Innovation to Stay Ahead in the Game

March 2, 2021
Next Post
Relying on bug bounties ‘not appropriate risk management’: Katie Moussouris

Relying on bug bounties 'not appropriate risk management': Katie Moussouris

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

Microsoft: We’ve found three more pieces of malware used by the SolarWinds attackers
Internet Security

Microsoft: We’ve found three more pieces of malware used by the SolarWinds attackers

March 6, 2021
Bug in Apple’s Find My Feature Could’ve Exposed Users’ Location Histories
Internet Privacy

Bug in Apple’s Find My Feature Could’ve Exposed Users’ Location Histories

March 6, 2021
Machine learning the news for better macroeconomic forecasting
Machine Learning

Reducing Blind Spots in Cybersecurity: 3 Ways Machine Learning Can Help

March 6, 2021
5 Tech Trends Redefining the Home Buying Experience in 2021 | by Iflexion | Mar, 2021
Neural Networks

5 Tech Trends Redefining the Home Buying Experience in 2021 | by Iflexion | Mar, 2021

March 6, 2021
Zigbee inside the Mars Perseverance Mission and your smart home
Internet Security

Zigbee inside the Mars Perseverance Mission and your smart home

March 6, 2021
Mazafaka — Elite Hacking and Cybercrime Forum — Got Hacked!
Internet Privacy

Mazafaka — Elite Hacking and Cybercrime Forum — Got Hacked!

March 6, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • Microsoft: We’ve found three more pieces of malware used by the SolarWinds attackers March 6, 2021
  • Bug in Apple’s Find My Feature Could’ve Exposed Users’ Location Histories March 6, 2021
  • Reducing Blind Spots in Cybersecurity: 3 Ways Machine Learning Can Help March 6, 2021
  • 5 Tech Trends Redefining the Home Buying Experience in 2021 | by Iflexion | Mar, 2021 March 6, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates