computer vision News - Page 25 of 26 - CNX Software

February 14, 2018 by Jean-Luc Aufranc (CNXSoft) - No Comments

Arm’s Project Trillium Combines Machine Learning and Object Detection Processors with Neural Network Software

We’ve already seen Neural Processing Units (NPU) added to Arm processors such as Huawei Kirin 970 or Rockchip RK3399Pro in order to handle the tasks required by machine learning & artificial intelligence in a faster or more power efficient way. Arm has now announced their Project Trillium offering two A.I. processors, with one ML (Machine Learning) processor and one OD (Object Detection) processor, as well as open source Arm NN (Neural Network) software to leverage the ML processor, as well as Arm CPUs and GPUs. Arm ML processor key features and performance: Fixed function engine for the best performance & efficiency for current solutions Programmable layer engine for futureproofing the design Tuned for advance geometry implementations. On-board memory to reduce external memory traffic. Performance / Efficiency – 4.6 TOP/s with an efficiency of 3 TOPs/W for mobile devices and smart IP cameras Scalable design usable for lower requirements IoT (20 […]

December 6, 2017December 6, 2017 by Jean-Luc Aufranc (CNXSoft) - 7 Comments

A Day at Chiang Mai Maker Party 4.0

The Chiang Mai Maker Party 4.0 is now taking place until December 9, and I went there today, as I was especially interested in the scheduled NB-IoT talk and workshop to find out what was the status about LPWA in Thailand. But there are many other activities planned, and if you happen to be in Chiang Main in the next few days, you may want to check out the schedule on the event page or Facebook. I’m going to go though what I’ve done today to give you a better idea about the event, or even the maker movement in Thailand. Booth and activity area should be the same over the 4 days, but the talks, open activity, and workshop will be different each day. Today, people could learn how to solder in the activity area. The even was not really big with manufacturers/sellers like ThaiEasyElec, INEX, or Gravitech closer […]

December 1, 2017December 1, 2017 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

$45 AIY Vision Kit Adds Accelerated Computer Vision to Raspberry Pi Zero W Board

AIY Projects is an initiative launched by Google that aims to bring do-it yourself artificial intelligence to the maker community by providing affordable development kits to get started with the technology. The first project was AIY Projects Voice Kit, that basically transformed Raspberry Pi 3 board into a Google Home device by adding the necessary hardware to support Google Assistant SDK, and an enclosure. The company has now launched another maker kit with AIY Project Vision Kit that adds a HAT board powered by Intel/Movidius Myriad 2 VPU to Raspberry Pi Zero W, in order to accelerate image & objects recognition using TensorFlow’s machine learning models. The kit includes the following items: Vision Bonnet accessory board powered by Myriad 2 VPU (MA2450) 2x 11mm plastic standoffs 24mm RGB arcade button and nut 1x Privacy LED 1x LED bezel 1x 1/4/20 flanged nut Lens, lens washer, and lens magnet 50 mil […]

November 30, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

AWS DeepLens is a $249 Deep Learning Video Camera for Developers

Amazon Web Services (AWS) has launched Deeplens, the “world’s first deep learning enabled video camera for developers”. Powered by an Intel Atom X5 processor with 8GB, and featuring a 4MP (1080p) camera, the fully programmable system runs Ubuntu 16.04, and is designed expand deep learning skills of developers, with Amazon providing tutorials, code, and pre-trained models. AWS Deeplens specifications: SoC – Intel Atom X5 Processor with Intel Gen9 HD graphics (106 GFLOPS of compute power) System Memory – 8GB RAM Storage – 16GB eMMC flash, micro SD slot Camera – 4MP (1080p) camera using MJPEG, H.264 encoding Video Output – micro HDMI port Audio – 3.5mm audio jack, and HDMI audio Connectivity – Dual band WiFi USB – 2x USB 2.0 ports Misc – Power button; camera, WiFi and power status LEDs; reset pinhole Power Supply – TBD Dimensions – 168 x 94 x 47 mm Weight – 296.5 grams The […]

November 24, 2017November 24, 2017 by Jean-Luc Aufranc (CNXSoft) - 10 Comments

Cheap Evil Tech – WiFi Deauther V2.0 Board and Autonomous Mini Killer Drones

Most technological advances usually improve life of people, and with the costs coming down dramatically over the years, available to more people. But technology can be used for bad, for example by governments and some hackers. Today, I’ve come across two cheap hardware devices that could be considered evil. The first one is actually pretty harmless and can be use for education, but disconnects you from your WiFi, which may bring severe physiological trauma to some people, but should not be life threatening, while the other is downright scary with cheap targeted killing machines. WiFi Deauther V2.0 board Specifications for this naughty little board: Wireless Module based on ESP8266 WiSoC USB – 1x Micro USB type changed, more stable. Expansion – 17-pin header with 1x ADC, 10x GPIOs, power pins Misc – 1x power switch, battery status LEDs Power Supply 5 to 12V via micro USB port Support for 18650 […]

November 22, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

Hisilicon Hi3559A V100ES is an 8K Camera SoC with a Neural Network Accelerator

Earlier today, I published a review of JeVois-A33 machine vision camera, noting that processing is handled by the four Cortex A7 cores of Allwinner A33 processor, but in the future we can expect such type of camera to support acceleration with OpenCL/Vulkan capable GPUs, or better, Neural network accelerators (NNA) such Imagination Tech PowerVR Series 2NX. HiSilicon already launched Kirin 970 SoC with such similarIP, except they call it an NPU (Neural-network Processing Unit). However, while looking for camera SoC with NNA, I found a list of deep learning processors, including the ones that go into powerful servers and autonomous vehicles, that also included a 8K Camera SoC with a dual core CNN (Convolutional Neural Network) acceleration engine made by Hisilicon: Hi3559A V100ES. Hisilicon Hi3559A V100ES specifications: Processor Cores 2x ARM Cortex A73 @ 2 GHz, 32 KB I cache, 64KB D cache or 512 KB L2 cache 2x ARM […]

November 22, 2017November 23, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

JeVois-A33 Linux Computer Vision Camera Review – Part 2: Setup, Guided Tour, Documentation & Customization

Computer Vision, Artificial Intelligence, Machine Learning, etc.. are all terms we hear frequently those days. JeVois-A33 smart machine vision camera powered by Allwinner A33 quad core processor was launched last year on Indiegogo to bring such capabilities in a low power small form factor devices for example to use in robotics project. The company improved the software since the launch of the project, and has now sent me their tiny Linux camera developer kit for review, and I’ve already checked out the hardware and accessories in the first post. I’ve now had time to test the camera, and I’ll explained how to set it up, test some of the key features via the provided guided tour, and show how it’s possible to customize the camera to your needs with one example. Getting Started with JeVois-A33 In theory, you could just get started by inserting the micro SD card provided with […]

October 24, 2017October 24, 2017 by Jean-Luc Aufranc (CNXSoft) - No Comments

JeVois Smart Machine Vision Camera Review – Part 1: Developer / Robotics Kit Unboxing

JeVois-A33 computer vision camera was unveiled at the end of last year through a Kickstarter campaign. Powered by an Allwinner A33 quad core Cortex A7 processor, and a 1.3MP camera sensor, the system could detect motion, track faces and eyes, detect & decode ArUco makers & QR codes, follow lines for autonomous cars, etc.. thanks to JeVois framework. Most rewards from KickStarter shipped in April of this year, so it’s quite possible some of the regular readers of this blog are already familiar the camera. But the developer (Laurent Itti) re-contacted me recently, explaining they add improves the software with Python support, and new features such as the capability of running deep neural networks directly on the processor inside the smart camera. He also wanted to send a review sample, which I received today, but I got a bit more than I expected, so I’ll start the review with an […]