最新大使亮点

探索学生大使们从事的项目,例如:机器人汽车、自动图像字幕、自然语言处理、自我意识的机器等。

33 个搜索结果

Code Sample: Optimizing Binarized Neural Networks on Intel® Xeon® Scalable Processors

发布时间:2018 年 8 月 14 日

In the previous article, we discussed the performance and accuracy of Binarized Neural Networks (BNN). We also introduced a BNN coded from scratch in the Wolfram Language. The key component of this neural network is Matrix Multiplication.

Knowledge Distillation with Keras*

发布时间:2018 年 8 月 9 日

The problem that we are facing right now is that we have built sophisticated models that can perform complex tasks, but the question is, how do we deploy such bulky models on our mobile devices for instant usage...

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Binary Neural Networks

发布时间:2018 年 8 月 8 日

Binary neural networks are networks with binary weights and activations at run time. At training time these weights and activations are used for computing gradients; however, the gradients and true weights are stored in...

Deep Learning Bengali Character Recognition from Real-World Images

发布时间:2018 年 8 月 2 日

The aim of this project is to apply deep learning models for recognition of Bengali characters and numerals. For training we used publicly available datasets. We also explore how to develop a complete Bengali character recognizer

Transfer Learning in Natural Language Processing

发布时间:2018 年 7 月 24 日

Transfer Learning was limited to computer vision up till now, but recent work shows that the impact can be extended almost everywhere, including natural language processing (NLP).

Using Natural Language Processing for Smart Question Generation

发布时间:2018 年 7 月 4 日

Introduction

Automatic question generation is part of Natural Language Processing (NLP). It is an area of research where many researchers have presented their work and is still an area under research to achieve higher accuracy. Many researchers...

heat maps of multiple lungs

Deep Learning: Build a Black Box Model for Medical Professionals

发布时间:2018 年 7 月 2 日

Building a Black Box Model Using Transfer Learning Introduction

In the 21st century, the years of big data and big innovations in medicine, we frequently hear about artificial intelligence (AI) solutions based on statistical and machine...

steel plate deformities examples

Use Machine Learning to Detect Defects on the Steel Surface

发布时间:2018 年 6 月 27 日

This article provides an effective and robust approach to detect and classify metal defects using computer vision and machine learning.

Part 1: Using Transfer Learning to Introduce Generalization in Models

发布时间:2018 年 6 月 25 日

This paper compares different ideas and methods that are used heavily in Machine Learning to determine what works best. These methods are prevalent in various domains of Machine Learning, such as Computer Vision and Natural Language Processing (NLP).

Improving Cycle-GAN using Intel® AI DevCloud

发布时间:2018 年 6 月 22 日

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

发布时间:2018 年 6 月 19 日

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

发布时间:2018 年 6 月 19 日

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

上次更新时间:2018 年 6 月 13 日视频时长:2 分钟

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

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

上次更新时间:2018 年 6 月 12 日视频时长:1 分钟

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

Deep Learning for Cryptocurrency Trading

上次更新时间:2018 年 6 月 12 日视频时长:2 分钟

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

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

上次更新时间:2018 年 6 月 12 日视频时长:4 分钟

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.

Bruna Maciel Pearson

Towards Autonomous UAV Flight in Cluttered Forestry Environments

上次更新时间:2018 年 6 月 11 日视频时长:2 分钟

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

Self Driving Vehicles and Risk Analysis

上次更新时间:2018 年 6 月 11 日视频时长:3 分钟

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

My Takeaways From Intel® AI DevCon

发布时间:2018 年 6 月 6 日

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...

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

发布时间:2018 年 5 月 24 日

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.

Brain Tumor Segmentation using Fully Convolutional Tiramisu Deep Learning Architecture

发布时间:2018 年 5 月 16 日

The aim of the work was to implement, train and evaluate the quality of automated brain tumor multi-label segmentation technique for Magnetic Resonance Imaging based on Tiramisu deep learning architecture.

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

发布时间:!datetime,更新时间: 2018 年 4 月 27 日

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

基于英特尔® AI DevCloud 的英特尔® Optimization for TensorFlow* 中的英特尔® 至强® 可扩展处理器架构和优化概述

发布时间:2018 年 4 月 27 日

使用基于英特尔® AI DevCloud 的英特尔® Optimization for TensorFlow 介绍英特尔® 至强® 可扩展处理器的架构和优化

MADRaS: A Multi-Agent DRiving Simulator

发布时间:2018 年 4 月 18 日

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

发布时间:2018 年 4 月 16 日

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.

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