250 Search Results

Refine by

    Results for:

AI News | Artificial Intelligence and Healthcare Data

Last updated: April 19, 2018

There are many opportunities for AI to help solve healthcare problems. Read “Artificial Intelligence and Healthcare Data” on the Intel AI Academy to learn how healthcare IT professionals can collaborate with healthcare experts.

AI UX | Ethics and Brand Trust

Last updated: April 17, 2018

This episode dives into how trust and ethics need to play a key role in the development of AI systems. 

Iceberg Classification Using Deep Learning on Intel® Architecture

Abstract Poor detection and drifting icebergs are major threats to marine safety and physical oceanography. As a result of these factors, ships can...

Unattended Baggage Detection Using Deep Neural Networks in Intel® Architecture

Published on July 14, 2017, updated April 16, 2018

In a world becoming ever more attuned to potential security threats, the need to deploy sophisticated surveillance systems is increasing. An...

Traffic Light Detection Using the TensorFlow* Object Detection API

Published on January 26, 2018, updated April 16, 2018

Abstract This case study evaluates the ability of the TensorFlow* Object Detection API to solve a real-time problem such as traffic light detection...

Pedestrian Detection Using Deep Neural Networks on Intel® Architecture

Published on January 30, 2018, updated April 16, 2018

Abstract This paper explains the process to train and infer the pedestrian detection problem using the TensorFlow* deep learning framework on Intel...

Speech Recognition Using Deep Learning on Intel® Architecture

This paper demonstrates how to train and infer the speech recognition problem using deep neural networks on Intel® architecture. A scratch training...

AI News | Introducing the Neuromorphic Research Community

Last updated: April 12, 2018

In this week's edition of edition of AI News you'll be introduced the new Neuromorphic Research Community Loihi.


AI UX | An Introduction

Last updated: April 10, 2018

Introducing AI UX! Over the next several week you will learn ten guidelines that can assist you as you develop, and design AI based systems. This episode also touches on the research that these 10 guidelines are based on!

Intel Optimized TensorFlow* Installation Guide

TensorFlow* is a predominately used machine learning framework in deep learning arena, demanding efficient utilization of computational resources. In...

Understanding NUMA using Intel® Optimization for Caffe*

Introduction In this article we demonstrate how Intel® VTune™ Amplifier can be used to identify and improve performance bottlenecks while running a...

Mapping Brain Connectivity Using Artificial Intelligence (AI)

Published on March 27, 2018

Techniques being developed by Panuwat Janwattanapong, using neural network inferences and natural language processing, are showing promising results...

Better Generative Modelling through Wasserstein GANs

Wasserstein GANs allow developers can train their discriminator to convergence. Doing this eliminates the need to balance generator updates with...

Artificial Intelligence (AI) Helps with Skin Cancer Screening

Published on March 26, 2018

Doctor Hazel, a service powered by artificial intelligence (AI) that helps screen for skin cancer in real time, powered by the Intel® Movidius™...

Intel® Processors for Deep Learning Training

On November 7, 2017, UC Berkeley, U-Texas, and UC Davis researchers published their results training ResNet-50* in a record time (as of the time of...

AI-Driven Test System Detects Bacteria In Water

Published on March 22, 2018

Using sophisticated pattern recognition and machine learning, an inexpensive AI-driven test system identifies harmful bacteria in water samples.

Screenshot from game video

Deploying Image Classifiers on Intel® Movidius™ Neural Compute Stick

Last updated: March 22, 2018

Learn how to profile, optimize, and deploy image classifiers on edge devices.

Use Transfer Learning For Efficient Deep Learning Training On Intel® Xeon® Processors

Introduction This is an educational white paper on transfer learning, showcasing how existing deep learning models can be easily and flexibly...

Detecting Diabetic Retinopathy Using Deep Learning on Intel® Architecture

Abstract Diabetic retinopathy (DR) is one of the leading causes of preventable blindness. This is rampant in people across the globe. Detecting it...

Mathematical Concepts and Principles of Naive Bayes

Published on June 8, 2017, updated March 14, 2018

Machine learning algorithms are becoming increasingly complex, and in most cases, are increasing accuracy at the expense of higher training-time...

Performance Optimization of Intel® Xeon® Processor Using Intel® Data Analytics Acceleration Library

Published on March 8, 2018

Abstract This article provides a comparative study of the performance of the Intel® Xeon® Gold processor when the Naive Bayes algorithm is taken...

Part 4: Long Short-Term Memory (LSTM) and Recurrent Neural Networks with BigDL

Last updated: March 8, 2018Video length: 19 min

In this video, we will take a look at Long Short Term Memory (LSTM) and Recurrent neural network (RNN) with BigDL.

Part 3: Transfer Learning for Image Classification with BigDL

Last updated: March 6, 2018Video length: 14 min

In this video, you will learn about transfer learning and how to apply it for image classification problem using BigDL.

Artificial Intelligence and Healthcare Data

Health professionals and researchers have access to plenty of healthcare data. However, the implementation of artificial intelligence (AI) technology...

Part 1: How to Deploy BigDL as a Docker* Container or Virtual Machine

Last updated: February 13, 2018Video length: 29 min

Step by step tutorial to get started with BigDL on Apache Spark*

Part 2: Build a Basic Neural Network Model with BigDL

Last updated: February 13, 2018Video length: 21 min

Step by step tutorial to build a basic neural network model, train and evaluate the model – all with BigDL on Apache Spark*

Visualising CNN Models Using PyTorch*

Before any of the deep learning systems came along, researchers took a painstaking amount of time understanding the data. Finding visual cues before...

Object Detection on Drone Videos using Neon™ Framework

Abstract The purpose of this article is to showcase the implementation of object detection1 on drone videos using Intel® optimized framework for...

Object Detection on Drone Videos using Caffe* Framework

Abstract The purpose of this article is to showcase the implementation of object detection1 on drone videos using Intel® Optimization for Caffe*2 on...

Face Detection with Intel® Distribution for Python*

Abstract Artificial Intelligence (AI) can be used to solve a wide range of problems, including those related to computer vision, such as image...

Intel® Math Kernel Library for Deep Learning Networks: Part 1–Overview and Installation

Learn how to install and build the library components of the Intel MKL for Deep Neural Networks.

Manage Deep Learning Networks with Intel® Optimization for Chainer*

Summary Chainer* is a Python*-based deep learning framework aiming at flexibility and intuition. It provides automatic differentiation APIs based...

Introducing DNN primitives in Intel® Math Kernel Library

    Deep Neural Networks (DNNs) are on the cutting edge of the Machine Learning domain. These algorithms received wide industry adoption in the late...

Deep Learning for Cancer Diagnosis: A Bright Future

In this article we explore how deep learning has been successfully applied to potential areas of oncology (the study of cancer diagnosis and...

Boosting Deep Learning Training & Inference Performance on Intel® Xeon® and Intel® Xeon Phi™ Processors

View PDF In this work we present how, without a single line of code change in the framework, we can further boost the performance for deep learning...