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Intel® VAS (Video Analytics Suite)

On 2020-09-18 18:00:00 UTC

We've added new video analytic sample applications that use tuned algorithms you can license for your own projects. Take a test drive

Tiny YOLO V3 Object Detection

On 2020-08-14 18:00:00 UTC

New Object Detection Sample using the Intel® Distribution of OpenVINO™ Toolkit.

OpenVINO updated to 2020.4

On 2020-07-15 18:00:00 UTC

Intel DevCloud for the Edge now features the Intel Distribution of OpenVINO Toolkit - 2020.4. For more information, view the release notes.

Synthetic Aperture Radar (SAR) Sample

On 2020-06-26 13:00:00 UTC

New Classification Sample that showcases classification of Synthetic Aperture Radar images using the Intel® Distribution of OpenVINO™ Toolkit

Accelerated Object Detection with Encrypted Model (C++)

On 2020-06-11 13:00:00 UTC

New Tutorial has been added that walks through the steps on how to use Intel® Distribution of OpenVINO™ Toolkit securely with encrypted models.

Learn Techniques To Migrate To/From Edge Devices

On 2020-06-06 13:00:00 UTC

New Tutorials have been added to help you migrate applications to Edge devices once you've experimented with them in DevCloud or import from edge devices to test on hardware in DevCloud.

OpenVINO updated to 2020.3 LTS

On 2020-06-4 13:00:00 UTC

Intel DevCloud for the Edge now features the Intel Distribution of OpenVINO Toolkit - 2020.3 LTS. For more information, view the release notes.

Clean Room Worker Safety

On 2020-05-15 13:00:00 UTC

New ONNX Object Detection Sample showcasing the detection of safety gear using ONNX Runtime EP for Intel® Distribution of OpenVINO™ toolkit.

New Speech Recognition C++ Sample

On 2020-05-08 13:00:00 UTC

A new sample that demonstrates the Speech Library API with OpenVINO™ inference engine for speech transcription.

DL Streamer tutorial

On 2020-05-05 13:00:00 UTC

A new tutorial demonstrating the workflow for building a modular GStreamer pipeline to perform object detection, tracking, and classification using the DL Streamer from the Intel® Distribution of OpenVINO™ toolkit.

OpenVINO updated to 2020.2

On 2020-04-23 16:00:00 UTC

Intel DevCloud for the Edge currently features the Intel Distribution of OpenVINO Toolkit - version 2020, release 2 (2020.2). For more information, view the release notes.

Edge node performance dashboards now featured in sample application

On 2020-04-13 15:12:00 UTC

Sample applications now feature dashboards for edge node performance metrics. Select 'view dashboard' after running inference on a target device within a Jupyter notebook.

Benchmark app to estimate inference performance

On 2020-04-02 19:00:00 UTC

A new tutorial demonstrating how to estimate the inference performance of your deep-learning models on supported devices.

Post-Optimization Toolkit

On 2020-04-02 19:00:00 UTC

Convert your model to INT8 format and optimize its performance using the Post-Optimization Toolkit in the Object Detection Python Sample.

OpenVINO updated to 2020.1

On 2020-02-17 20:00:00 UTC

Intel® DevCloud for the Edge currently features the Intel® Distribution of OpenVINO™ Toolkit, version 2020.1.

" Because we serve customers with so many different needs, it’s important to quickly achieve the right balance of price and performance for each of our applications. Intel® DevCloud for the Edge lets us test multiple platforms in parallel. That’s a lot of time savings—and time is money—so it’s a no-brainer. "

- Eduard Vazquez, Research Technical Manager, AnyVision

AnyVision Solution Brief >

" Because developers can quickly evaluate the performance of their applications in multiple edge computing systems by using Intel® DevCloud for the Edge, they can not only shorten the inspection time to go to market, they can also expect tremendous benefits in terms of investment and maintenance in verification equipment. We are confident that Intel DevCloud for the Edge will accelerate and streamline operations and create new value for more IoT businesses and for more customers. "

- Tomohiro Nagao, Senior Manager, Hitachi, Ltd., Healthcare Business Unit

Hitachi Solution Brief >

" Using the Intel® DevCloud for Edge allows Luxonis to iterate on our products seamlessly in the physical world, with real-world experimentation and data collection, as well as in the cloud environment for fast improvement of our neural models and computer vision flow. This results in our customers typically getting their proof of concepts up and running in less than one week and products maturing for market in just a few months. DevCloud for the Edge allows us to evaluate performance without the need of hardware in hand, and can iterate across hardware, software, AI, training iterations, and overall performance easily. Leveraging these kinds of tools, we currently have over 100 customers building products off of our platform, which covers over 20 verticals, including e-mobility, cargo - air and ground, food processing, agriculture (in-field, farming and ranching), defense, safety systems (in manufacturing, oil/gas, etc.) to name just a few. "

- Brandon Gilles, CEO, Luxonis Embedded CV & AI

" Rosmart provides automatic defects detection machines to do the visual inspection work. It can always keep the high quality standard, high inspection efficiency, and low labor cost. "

- Alex Zhang, R&D director, Guangdong Rosmart Technology Co., Ltd.

Rosmart Solution Brief >

" Because of the user experience we are trying to achieve, it is important to find the perfect balance of price and performance for each of our products. Though Intel® DevCloud for the Edge and its well prepared tools and environment, we were able to decrease the time it took to do a wide array of hardware tests on our interactive digital signage solutions, like Intelligent Label. "

- Ryota Tone, Content Business Division, Business Development Department Manager, SB Creative Corp.

" The Intel® OpenVINO toolkit was very helpful to optimize our AI model, as it helped accelerate the overall computation, while fully maintaining the model accuracy. Moreover the ability to run it in the Intel® DevCloud for the Edge enabled us to optimize inferencing over a wide range of Intel® processors without having us invest in procuring and maintaining the physical hardware platforms. "

- Zia Manzur, COO, Tech for Social Impact

Technology for Social Impact Solution Brief >

" The results from our exercise in Intel® DevCloud for the Edge show that neural network computing performance on a CPU now matches a GPU. These performance benchmarks are constantly improving, thanks to new, innovative tools. Now, advanced edge inference solutions like ours are feasible with CPUs, allowing us to run our solution as a real-time IoT application operating on Intel® Xeon® processors at multiple stores. "

- Erdem Yoruk, Chief Scientist, Vispera Information Technologies

Vispera Solution Brief >

" Intel® DevCloud for the Edge allows us to choose our hardware configuration to optimize training, enabling us to create vertical CV models for each customer’s needs. "

- Reinier van Kleij, CTO, WonderStore

WonderStore Solution Brief >