Latest Ambassador Highlights

Explore the projects that student ambassadors are working on such as robotic cars, automatic image captions, natural language processing, self-aware machines, and much more.

24 Search Results

Improving Cycle-GAN using Intel® AI DevCloud

Published on June 22, 2018

In this article, we will see some scope for optimization in Cycle-GAN for unpaired image-to-image translation, and come up with a new architecture.

Keras* Implementation of Siamese-like Networks

Published on June 19, 2018

This guide will help you to write complex neural networks such as Siamese networks in Keras. It also explains the procedure to write your own custom layers in Keras.

Understanding Capsule Network Architecture

Published on June 19, 2018

Capsule networks (CapsNet) are the new architecture in neural networks, an advanced approach to previous neural network designs, particularly for computer vision tasks. To date, convolutional neural networks (CNN) have...

RAIL: Risk-Averse Imitation Learning System

Last updated: June 13, 2018Video length: 2 min

Present a Risk-Averse Imitation Learning (RAIL) algorithm as an alternative to Generative Adversarial Imitation Learning (GAIL) for improved reliability in risk-sensitive applications.

Deep Learning for Cryptocurrency Trading

Last updated: June 12, 2018Video length: 2 min

The project Deep Learning for Cryptocurrency Trading is focused on utilizing sentiment analysis on social outputs related to Cryptocurrencies on Reddit* and Twitter*.

Automating Wildlife Image Processing Using IoT and the Intel® Movidius™ Neural Compute Stick

Last updated: June 12, 2018Video length: 1 min

The design and implementation of Where's The Bear (WTB), an end-to-end, distributed, IoT system for wildlife monitoring.

A CLass-Enhanced Attentive Response (CLEAR) Approach to Understand Deep Neural Networks

Last updated: June 12, 2018Video length: 4 min

We propose CLass-Enhanced Attentive Response (CLEAR): an approach to visualize and understand the decisions made by deep neural networks (DNNs) given a specific input.

Self Driving Vehicles and Risk Analysis

Last updated: June 11, 2018Video length: 3 min

We show a method to create a guidance solution based upon system risk for a system’s goal.

Bruna Maciel Pearson

Towards Autonomous UAV Flight in Cluttered Forestry Environments

Last updated: June 11, 2018Video length: 2 min

An approach for automatic trail navigation with an Unmanned Aerial Vehicle (UAV).

My Takeaways From Intel® AI DevCon

Published on June 6, 2018

Intel Artificial Intelligence Developer Conference (AIDC) was a two-day conference that took place at the San Francisco Palace of Fine Arts on May 23-24, 2018. Unlike most conferences held by tech companies, this conference was highly technical...

Intel Movidius Neural Compute Stick Workflow

Bringing Artificial Intelligence to the Edge

Published on June 3, 2018

We encounter artificial intelligence in almost all our daily tasks: speech-to-text, photo tagging technology, fingerprint recognition, spam classification. We see it contributing to cutting-edge innovations: precision...

Using the Intel® Distribution for Python* to Solve the Scene-Classification Problem Efficiently

Published on May 24, 2018

This article shows how to get acquainted with image and scene categorization. Firstly, to extract the image features, then prepare a classifier using the training samples, and finally to assess the classifier on a test set.

Solving Latency Challenges in End-to-End Deep Learning Applications

Published on May 10, 2018

Intel® Student Ambassador David Ojika Uses Intel® Movidius™ Myriad™ 2 Technology for Specialized Vision Processing at the Edge


The Intel® Student Ambassador Program for...

Machine Learning and Mammography

Published on May 3, 2018

This article shows how deep learning can be used to be able to detect invasive ductal carcinoma (IDC) in unlabeled histology images. It shows how to train a convolutional neural network using TensorFlow* and transfer learning using a dataset of negative and positive histology images.

Review of Architecture and Optimization on Intel® Xeon® Scalable Processors in context of Intel® Optimization for TensorFlow* on Intel® AI DevCloud

Published on January 23, 2018, updated April 27, 2018

Present the architecture and optimization on Intel® Xeon® Scalable Processors (CPU) using Intel® Optimization for TensorFlow* on the Intel® AI DevCloud

MADRaS: A Multi-Agent DRiving Simulator

Published on April 18, 2018

This article presents MADRaS: Multi-Agent DRiving Simulator. It is a multi-agent version of TORCS, a racing simulator popularly used for autonomous driving research by the reinforcement learning and imitation learning communities.

Training an Agent to Play Pong* Using neon™ Framework

Published on April 16, 2018

This article showcases the implementation of an agent to play the game Pong* using an Intel® architecture-optimized neon™ framework, and to serve as an introduction to the Policy Gradients algorithm.

Better Generative Modelling through Wasserstein GANs

Published on March 26, 2018

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

Visualising CNN Models Using PyTorch*

Published on February 9, 2018

Before any of the deep learning systems came along, researchers took a painstaking amount of time understanding the data. Finding visual cues before handing it off to an algorithm. But right now, we almost always feed our data into a transfer...

AI Student Ambassador Devinder Kumar: Applying Deep Learning in the Healthcare and Finance Sectors

Published on February 7, 2018

The Intel® Student Ambassador Program was created to work collaboratively with students at innovative schools and universities doing great work in the Machine Learning and Artificial Intelligence space. I had the opportunity to get to know one of...

Functional Connectivity of Epileptic Brains: Investigating Connectivity of Epileptic Brain - Week 1 Update

Published on November 14, 2017

This blog post introduces the utilization of connectivity investigation to epileptic brains. We will show the fundamental steps to process EEG data including pre-processing, applying necessary filters, and perform a basic connectivity extraction...

Functional Connectivity of Epileptic Brains: Preprocessing EEG Data - Week 2 Update

Published on November 14, 2017

EEG data can be recorded with many different file types depending on the instrument and the institution.  The file type in this research that we will be working with is the simple text file containing EEG data.


Functional Connectivity of Epileptic Brains: Extracting Functional Connectivity - Week 3 Update

Published on November 14, 2017

In the previous week we applied preprocessing techniques to obtain the cleaned EEG data. This week we are introducing how to extract functional connectivity from the EEG data. Functional connectivity is defined as a study of the correlation of...

AI Student Ambassador Ngesa Marvin: A Community Advocate in Kenya

Published on May 30, 2017

Predicting the exact location of harmful weeds in Lake Victoria is a challenge but with Google Earth and wind data, Intel® Student Ambassador Ngesa Marvin thinks he can help eradicate them.  Ngesa started his journey into technology with a single...