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CEI-Europe announces the 100th Anniversary Digital Image Sensors Course by Professor Albert J.P. Theuwissen. Since 1999, Professor Theuwissen has trained and helped engineers across the world to enhance their skills and know-how about Solid-State Imaging, Image Sensors Technology, and Digital Camera Systems.

On November 13-15, 2017 in Barcelona, Spain (or in Catalonia?), he will train the 100th group of engineers for CEI-Europe.

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Huaian Imaging Device Manufacturer Corporation (HIDM) is a new image sensor startup in China that starts big - from building its own 12-inch CIS wafer fab. The CEO and founder of HIDM is ST Hsia, previously served as Global VP of SMIC, VP of NEC, CEO of Ether, and Chief Director of PROMOS & VIS. There is very little known about the new company founded on Jan. 19, 2016:

"Startup Huaian Imaging Device Manufacturer (HIDM) plans to build a 12-inch fab in Huaian, Jiangsu province, with production capacity set at 20,000 wafers monthly. Founded in 2016, HIDM specializes in the design and manufacture of CMOS image sensor devices."

Apparently, it is the licensee of ON Semi discontinued mobile products and the related IP:

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IC Insights report on optoelectronics market predicts an acceleration in image sensor sales growth:

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iFixit publishes a nice video analyzing iPhone X Face ID operation in IR light and attempts to trick it:

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TechInsights is quick to publish iPhone X Face ID hardware internals, with more details to follow:


iFixit too publishes its first teardown pictures, including well-cushioned dual rear camera:


iFixit publishes an IR video showing how the IR pattern projector flashes:

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Engadget: Sony develops "New Concept Cart SC-1" equipped with image sensors on all four sides of the vehicle. These 35mm full-frame BSI sensors are said to be able to see better than the human eye and open up a number of special features. Their ultra-high sensitivity is said to give the driver an unobstructed view even when driving at night without headlights. The image sensors allow users to take in their surroundings, eliminating the need for windows. SC-1's integrated image sensors provide a 360-degree view of all directions to give awareness of the car environment.

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Korea-based Nextchip publishes a video about its automotive imaging and vision processor:

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Embedded Vision Alliance publishes a preview of LG Senior Director of Technology and Product Planning Paul Gallagher talk on "Coming Shift from Image Sensors to Image Sensing":


TechInsights publishes a teardown report of Huawei flagship smartphone Mate 10. Its cameras cost about 12% of the total cost, not including a ToF module:

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Luminous Landscape publishes an article by Doug Peterson on the recently announced Phase One Trichromatic image sensor explaining the science behind it. There is a striking difference between the marketing presentation and what has been really done.

Here is how Phase One marketing presents Trichromatic color filter:


However, the real color response looks quite different:


The main color filter improvements developed together with Sony are:

• The amount of overlap between the red, green, and blue spectral responses is decreased and is steeper
• The improved “tail clipping” cleans color contamination
• Near-UV cut
• Colors balanced with respect to how much light pixels see

Thanks to TG for the pointer!

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HRL Laboratories receives an award from the Intelligence Advanced Research Projects Activity (IARPA), within the Office of the Director of National Intelligence, to develop spherically curved short-wave (SWIR) and medium wave (MWIR) infrared image sensors. This research will build on curved visible-light image sensor technology developed at HRL. The goal of the 12-month program is to develop fundamental technology and gain a better understanding of the effects of the bending process on the performance of III-V semiconductor SWIR and MWIR image sensors.

"Infrared sensors and their optics have different challenges than visible light imagers,” said Geoff McKnight, HRL’s principal investigator on the project. “One of which is that they often must be operated at very low temperatures, which introduces thermal stresses from the contraction of the sensors. After curving the sensors, we will have to cool them to cryogenic temperature for operation, and the combination of the thermal stresses and bending stresses may potentially degrade or fracture the detectors.”

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Fujitsu develops 3D camera to improve scoring in gymnastics, as shown in the company's Youtube video:

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Imec Magazine article "Image sensor combining the best of different worlds" by Jonathan Borremans and Piet De Moor presents the BSI TDI image sensor based on CCD-in-CMOS process:

TDI principle, using 8 rows of pixels

Time delay integration using CCD-in-CMOS

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AutoSens TV Youtube channel publishes interviews from demo session at the conference. Some interesting examples:

Beat de Coi, CEO of ESPROS Photonics:



SensL's Edel Cashman explains how SiPM sensors could be used in lidar of the future:



Tarek Lule and Sylvie Gounet from ST demonstrate LED flicker-free imaging solutions:



Chronocam CEO Luca Verre talks about the company and the technology:



Geoff Ballew from On Semi talks about sensor fusion:

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Oprics.org: Ford autonomous driving division Argo.ai acquires LiDAR startup Princeton Lightwave developing "Geiger-mode" flash LiDAR.

Argo's CEO Bryan Salesky says: "We can’t talk about a future of self-driving cars without mentioning LiDAR technology — and we won’t be able to build that future without it. These sensors are crucial to creating a three-dimensional view of the world that helps autonomous vehicles find where they are on the road and detect other vehicles, pedestrians and cyclists.

To accelerate our mission to realize the self-driving future, Argo has acquired Princeton Lightwave, a company with extensive experience in the development and commercialization of LiDAR sensors."

The receive side of GeigerCruiser ADAS LiDAR is based on an array of "Geiger-mode avalanche photodiode (GmAPD)" working in 1.06um and 1.55um bands:

"The camera can collect sub-nanosecond resolution timestamps for arbitrarily long periods of time as well as emulate gated (framed) operation, and the sensor can generate timestamps at rates of nearly 1 Gsamples/second. The sensor engine of the camera is a focal plane array (FPA) with hexagonal geometry pixels on a 65.8 µm pixel pitch formatted in a rectangular imaging area of 2.1 mm x 1.8 mm. The FPA is assembled by flip-chip bonding an InP/InGaAsP GmAPD detector array to a custom CMOS readout integrated circuit (ROIC) and then attaching a GaP microlens array to the GmAPD array to provide a high optical fill factor. The hermetically sealed FPA housing has an integrated two-stage thermoelectric cooler to maintain appropriate operating temperature with closed-loop feedback adjustment."

The company presents a video demo of the ADAS LiDAR: "The video contains point clouds collected and processed in real-time from the GeigerCruizer Demo System as it was driven in the vicinity of our headquarters in Cranbury NJ. Objects are detected beyond 300 meters and at reflectances of 10%, with angular resolutions to 1 mrad. In addition, imaging is shown in inclement weather conditions, such as snow and fog, as well as through obscurants such as water and dirt on the GeigerCruizer’s window."



PRNewswire: In another LiDAR news, MEMS scanning LiDAR startup Innoviz expands its series B investing round by $8m with Samsung Catalist and Korean branch of SoftBank joining this round. Together this brings the B round to $73m, added to $9m raised in round A.

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Sony reports quarterly earning results with a nice increase in its image sensors sales and outlook:

"We have upwardly revised our sales forecast by 20 billion yen due to an increase in our forecast for unit sales of image sensors for mobile products, compared with the August forecast. Primarily due to this increase in sales, we have upwardly revised our forecast for operating income by 20 billion yen to 150 billion yen."


Sony specifically emphasizes the automotive image sensor it has introduced recently:

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MEMS Drive publishes a short video on its OIS operation:

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GlobeNewsWire: TowerJazz partners with Changchun Changguang Yuanchen Microelectronics Technology Inc. (YCM), a BSI process manufacturer based in Changchun, China to provide the BSI processing for CMOS sensor wafers manufactured by TowerJazz. This is the first time BSI will be offered by a foundry to the high-end photography market, including large formats requiring stitching.

The partnership will allow TowerJazz to serve its customers with BSI technology in mass production, at competitive prices, starting in the middle of 2018. The new BSI technology is aimed to high-end photography, automotive, AR/VR, and other CIS markets. YCM provides the BSI processing for both 200mm and 300mm CIS wafers.

The new partnership also provides the roadmap for wafer stacking, including state-of-the-art pixel level wafer stacking.

"TowerJazz is recognized worldwide as the leader of CMOS image sensor manufacturing platforms for high-end applications," said Dabing Li, YCM CEO. "The collaboration with TowerJazz will certainly allow us to bring unique and high value technology to the market quickly and in high volume, especially to the growing Chinese market where TowerJazz already plays a significant role."

"I am thrilled with the capabilities we developed with YCM, supporting our continued leadership in many different high-end growing markets. In addition, the excellent collaboration with YCM enables us further penetration into this very fast growing high-end CMOS camera market in China," said Avi Strum, SVP and GM, CMOS Image Sensor Business Unit. "I have very high confidence in the technical capabilities of this partnership."

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New Zealand-based Chronoptics releases PixelScope instrument measuring pixel timing response parameters:

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Mobileye CTO Amnon Shashua talks about autonomous car sensing and processing of the data to ensure the safety at 2017 World Knowledge Forum in Seoul, South Korea. The talk does not directly refer to the imaging but rather presents the way to overcome the processing of the huge amount of imaging data over 30 billion of miles while still ensuring the safety of autonomous driving:

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Samsung publishes a paper "Outdoor Operation of Structured Light in Mobile Phone" by Byeonghoon Park, Yongchan Keh, Donghi Lee, Yongkwan Kim, Sungsoon Kim, Kisuk Sung, Jungkee Lee, Donghoon Jang, Youngkwon Yoon presented at The IEEE International Conference on Computer Vision (ICCV), 2017.

"Active Depth Camera does not operate well especially outdoors because signal light is much weaker than ambient sunlight. To overcome this problem, Spectro-Temporal Light Filtering, adopting a light source of 940nm wavelength, has been designed. In order to check and improve outdoor depth quality, mobile phones for proof-of-concept have been implemented with structured light depth camera enclosed. We present its outdoor performance, featuring a 940nm vertical cavity surface emitting laser as a light source and an image sensor with a global shutter to reduce ambient light noise. The result makes us confident that this functionality enables mobile camera technology to step into another stunning stage."


Mantis Vision Coded Light algorithm was used in this work. The company publishes a video on its technology:



Meanwhile, SINTEF Digital publishes an Optics Express paper "Design tool for TOF and SL based 3D cameras" by Gregory Bouquet, Jostein Thorstensen, Kari Anne Hestnes Bakke, and Peter Risholm. A structured light camera excels at short range, such as Apple Face ID, while a ToF camera is a better fit for long range applications, such as Google Tango:

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Bloomberg publishes some info about iPhone X depth camera production difficulties:

"The 3-D sensor has three key elements: a dot projector, flood illuminator and infrared camera. The flood illuminator beams infrared light, which the camera uses to establish the presence of a face. The projector then flashes 30,000 dots onto the face which the phone uses to decide whether to unlock the home screen. The system uses a two-stage process because the dot projector makes big computational demands and would rapidly drain the battery if activated as frequently as the flood illuminator.

The dot projector is at the heart of Apple’s production problems. Precision is key. If the microscopic components are off by even several microns, a fraction of a hair’s breadth, the technology might not work properly, according to people with knowledge of the situation.

The fragility of the components created problems for LG Innotek Co. and Sharp Corp., both of which struggled to combine the laser and lens to make dot projectors. To boost the number of usable dot projectors and accelerate production, Apple relaxed some of the specifications for Face ID, according to a person with knowledge of the process. As a result, it took less time to test completed modules, one of the major sticking points, the person said.

To make matters worse, Apple lost one of its laser suppliers early on. Finisar Corp. failed to meet Apple’s specifications in time for the start of production. That left Apple reliant on fewer laser suppliers: Lumentum Holdings Inc. and II-VI Inc."

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BusinessWire: ON Semi AR0239 1080p90 CMOS sensor with 3μm BSI pixels uses an improved NIR process, includes DR-Pix technology and gives a 21% improvement in responsivity and a 10% improvement in QE versus the device’s predecessor.

The new sensor delivers 1080p video at 90fps or two- or three-exposure 1080p HDR video at up to 30fps. Engineering samples are available now with full production planned for November 2017.

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SeekingAlpha publishes ST Q3 2017 earnings call transcript. Few quotes on the image sensor business:

"Let's move now to our Imaging Product Division, which we report in Others. Imaging registered very strong sequential revenue growth, reflecting the initial ramp in wireless applications of ST's new program, including the company's Time-of-Flight and new specialized imaging technologies. Other revenues more than doubled in the third quarter.

...we can confirm that based on current visibility, ...the Imaging division anticipate sequential revenues growth from the third into the fourth quarter and anticipate a double-digit year-over-year growth in the fourth quarter in respect to the fourth quarter of the prior year.

...we target the LIDAR device, which are really a key enabling component of the overall smart driving application. And our technology is really a key competitive factor for us to target this kind of LIDAR activity definitively."

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IEDM 2017, to be held on Dec. 2-6 in San Francisco, publishes its agenda. Here is the list of image sensor related materials, starting from 3 Sony papers:

3.2 Pixel/DRAM/logic 3-layer stacked CMOS image sensor technology (Invited)
H. Tsugawa, H. Takahashi, R. Nakamura, T. Umebayashi, T. Ogita, H. Okano, K. Iwase, H. Kawashima, T. Yamasaki*, D. Yoneyama*, J. Hashizume, T. Nakajima, K. Murata, Y. Kanaishi, K. Ikeda*, K. Tatani, T. Nagano, H. Nakayama*, T. Haruta and T. Nomoto, Sony Semiconductor
We developed a CMOS image sensor (CIS) chip, which is stacked pixel/DRAM/logic. In this CIS chip, three Si substrates are bonded together, and each substrate is electrically connected by two-stacked through-silica vias (TSVs) through the CIS or dynamic random access memory (DRAM). We obtained low resistance, low leakage current, and high reliability characteristics of these TSVs. Connecting metal with TSVs through DRAM can be used as low resistance wiring for a power supply. The Si substrate of the DRAM can be thinned to 3 μm, and its memory retention and operation characteristics are sufficient for specifications after thinning. With this stacked CIS chip, it is possible to achieve less rolling shutter distortion and produce super slow motion video.

16.4 Near-infrared Sensitivity Enhancement of a Back-illuminated Complementary Metal Oxide Semiconductor Image Sensor with a Pyramid Surface for Diffraction Structure
I. Oshiyama, S. Yokogawa, H. Ikeda, Y. Ebiko, T. Hirano, S. Saito, T. Oinoue, Y. Hagimoto, H. Iwamoto, Sony Semiconductor
We demonstrated the near-infrared (NIR) sensitivity enhancement of back-illuminated complementary metal oxide semiconductor image sensors (BI-CIS) with a pyramid surface for diffraction (PSD) structures on crystalline silicon and deep trench isolation (DTI). The incident light diffracted on the PSD because of the strong diffraction within the substrate, resulting in a quantum efficiency of more than 30% at 850 nm. By using a special treatment process and DTI structures, without increasing the dark current, the amount of crosstalk to adjacent pixels was decreased, providing resolution equal to that of a flat structure. Testing of the prototype devices revealed that we succeeded in developing unique BI-CIS with high NIR sensitivity.

16.1 An Experimental CMOS Photon Detector with 0.5e- RMS Temporal Noise and 15µm pitch Active Sensor Pixels
T. Nishihara, M. Matsumura, T. Imoto, K. Okumura, Y. Sakano, Y. Yorikado, Y. Tashiro, H. Wakabayashi, Y. Oike and Y. Nitta, Sony Semiconductor
This is the first reported non-electron-multiplying CMOS Image Sensor (CIS) photon-detector for replacing Photo Multiplier Tubes (PMT). 15µm pitch active sensor pixels with complete charge transfer and readout noise of 0.5 e- RMS are arrayed and their digital outputs are summed to detect micro light pulses. Successful proof of radiation counting is demonstrated.

8.6 High-Performance, Flexible Graphene/Ultra-thin Silicon Ultra-Violet Image Sensor
A. Ali, K. Shehzad, H. Guo, Z. Wang*, P. Wang*, A. Qadir, W. Hu*, T. Ren**, B. Yu*** and Y. Xu, Zhejiang University
*Chinese Academy of Sciences, **Tsinghua University, ***State University of New York
We report a high-performance graphene/ultra-thin silicon metal-semiconductor-metal ultraviolet (UV) photodetector, which benefits from the mechanical flexibility and high-percentage visible light rejection of ultra-thin silicon. The proposed UV photodetector exhibits high photo-responsivity, fast time response, high specific detectivity, and UV/Vis rejection ratio of about 100, comparable to the state-of-the-art Schottky photodetectors

16.2 SOI monolithic pixel technology for radiation image sensor (Invited)
Y. Arai, T. Miyoshi and I. Kurachi, High Energy Accelerator Research Organization (KEK)
SOI pixel technology is developed to realize monolithic radiation imaging device. Issues of the back-gate effect, coupling between sensors and circuits, and the TID effect have been solved by introducing a middle Si layer. A small pixel size is achieved by using the PMOS and NMOS active merge technique.

16.3 Back-side Illuminated GeSn Photodiode Array on Quartz Substrate Fabricated by Laser-induced Liquidphase Crystallization for Monolithically-integrated NIR Imager Chip
H. Oka, K. Inoue, T. T. Nguyen*, S. Kuroki*, T. Hosoi, T. Shimura and H. Watanabe, Osaka University, *Hiroshima University
Back-side illuminated single-crystalline GeSn photodiode array has been demonstrated on a quartz substrate for group-IVbased NIR imager chip. Owing to high crystalline quality of GeSn array formed by laser-induced liquid-phase crystallization technique, significantly enhanced NIR photoresponse with high responsivity of 1.3 A/W was achieved operated under backside illumination

16.5 Industrialised SPAD in 40 nm Technology
S. Pellegrini, B. Rae, A. Pingault, D. Golanski*, S. Jouan*, C. Lapeyre** and B. Mamdy*, STMicroelectronics,*TR&D, *CEA-Leti, Minatec
We present the first mature SPAD device in advanced 40 nm technology with dedicated microlenses. A high fill factor >70% is reported with a low DCR median of 50cps at room temperature and a high PDP of 5% at 840nm. This digital node is portable to a 3D stacked technology.

16.6 A Back-Illuminated 3D-Stacked Single-Photon Avalanche Diode in 45nm CMOS Technology
M.-J. Lee, A. R. Ximenes, P. Padmanabhan, T. J. Wang*, K. C. Huang*, Y. Yamashita*, D. N. Yaung* and E. Charbon
Ecole Polytechnique Fédérale de Lausanne (EPFL), *Taiwan Semiconductor Manufacturing Company (TSMC)
We report on the world's first back-illuminated 3D-stacked single-photon avalanche diode (SPAD) in 45nm CMOS technology. This SPAD achieves a dark count rate of 55.4cps/µm2, a maximum photon detection probability of 31.8% at 600nm, over 5% in the 420-920nm wavelength range, and timing jitter of 107.7ps at 2.5V excess bias voltage and room temperature. To the best of our knowledge, these are the best results ever reported for any back-illuminated 3D-stacked SPAD technology.

26.2 High-yield passive Si photodiode array towards optical neural recording
D. Mao, J. Morley, Z. Zhang, M. Donnelly, and G. Xu, *University of Massachusetts Amherst
We demonstrate a high yield, passive Si photodiode array, aiming to establish a miniaturized optical recording device for in-vivo use. Our fabricated array features high yield (>90%), high sensitivity (down to 32 μW/cm2), high speed (1000 frame per second by scanning over up to 100 pixels), and sub-10uW power.

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Alex Kipman, Microsoft 3D vision architect, and Matthew Lapsen, GM of Xbox Devices Marketing told in an interview with Co.Design that Microsoft is discontinuing Kinect ToF device. While the Kinect as a standalone product leaves the market, Microsoft is not abandoning the ToF technology. It's currently being used in Microsoft Hololens, with its new version is being developed. Kinect’s ToF team has been re-targeted to build other Microsoft products, including the Cortana voice assistant, the Windows Hello biometric facial ID system, and a context-aware user interface for the future that Microsoft dubs Gaze, Gesture, and Voice (GGV).

Since its lunch in 2010, Microsoft has sold 35 million Kinect units, making it the best selling 3D camera, until iPhone X sales reach that milestone sometime next year. In the first few years, Kinect was based on Primesense structured light technology. According to AppleInsider, Microsoft sold 24 million of the PrimeSense-powered Kinect-1 by February of 2013, a little over two years after it launched. This leaves 11 million units for Canesta ToF-based Kinect-2 device.

Other interesting info is the power consumption progress of Micosoft 3D camera over the years: 50W in the structured light-based Kinect-1, 25W in ToF Kinect-2, 1.5W in ToF-based Hololens.

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Chinese smartphone maker Doogee publishes a Youtube video demoing 3D face unlock in its Mix 2 smartphone:

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BBC Click channel on Youtube publishes a report from Ishikawa Watanabe Lab in University of Tokyo:

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BusinessWire: ON Semiconductor announces Hayabusa CMOS sensor platform for automotive applications such as ADAS, mirror replacement, rear and surround view systems and autonomous driving. The Hayabusa platform features a 3.0um BSI pixel design that delivers a charge capacity of 100,000e-, said to be highest in the industry, on-chip Super-Exposure capability for HDR with LED flicker mitigation (LFM), and real-time functional safety and automotive grade qualification.

“The Hayabusa family enables automakers to meet the evolving standards for ADAS such as European NCAP 2020, and offer next-generation features such as electronic mirrors and high-resolution surround view systems with anti-flicker technology. The scalable approach of the sensors from ½” to ¼” optical sizes reduces customer development time and effort for multiple car platforms, giving them a time-to-market advantage.” said Ross Jatou, VP and GM of the Automotive Solutions Division at ON Semiconductor. “ON Semiconductor has been shipping image sensors with this pixel architecture in high-end digital cameras for cinematography and television. We are now putting this proven architecture into new sensors developed from the ground up for automotive standards.”

The high charge capacity of this pixel design enables every device in the Hayabusa family to deliver Super-Exposure capability, which results in 120dB HDR images with LFM without sacrificing low-light sensitivity. With the widespread use of LEDs for front and rear lighting as well as traffic signs, the LFM capability of the platform makes certain that pulsed light sources do not appear to flicker, which can lead to driver distraction or, in the case of front facing ADAS, the misinterpretation of a scene by machine vision algorithms.

The first product in this family, the 2.6MP AR0233 CMOS sensor, is capable of running 1080p at 60 fps. Samples are available now to early access customers.

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Digitimes sources say that Sony efforts to penetrate automotive imaging market are to start to bear fruits in 2018:

"Sony is looking to allocate more of its available production capacity for CIS for advanced driver assistance systems (ADAS) and other automotive electronics applications in a move to gradually shift its focus from smartphones and other mobile devices, said the sources. Currently, about half of Sony's CIS capacity is being reserved by the world's first-tier handset vendors.

Mobile devices remain the largest application for CIS, but self-driving vehicles have been identified by CIS suppliers as the "blue ocean" and will overtake mobile devices as the leading application for CIS, the sources indicated. CIS demand for ADAS will be first among all auto electronics segments set to boom starting 2018, the sources said."

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BusinessWire: Renesas, Australian Semiconductor Technology Company Pty Ltd (ASTC), and VLAB Works, a subsidiary of ASTC, announce a joint development of the VLAB/IMP-TASimulator virtual platform (VP) for Renesas’ R-Car V3M, an automotive SoC for ADAS and in-vehicle infotainment systems. The VP simulates image recognition and cognitive IPs in the R-Car V3M SoC and realizes embedded software development using a PC only, which enables the VP to shorten development time as well as improve software quality.

BrainChip Holdings announces that it has shipped its first BrainChip Accelerator card to a major European automobile manufacturer.

As the first commercial implementation of a hardware-accelerated spiking neural network (SNN) system, BrainChip Accelerator will be evaluated for use in ADAS and Autonomous Vehicle applications.

BrainChip Accelerator is said to increase the performance of object recognition provided by BrainChip Studio software and algorithms. The low-power accelerator card can detect, extract and track objects using a proprietary SNN technology. It provides a 7x improvement in images/second/watt, compared to traditional convolutional neural networks accelerated by GPUs.

Bob Beachler, BrainChip’s SVP for Marketing and Business Development, said: “Our spiking neural network provides instantaneous “one-shot” learning, is fast at detecting, extracting and tracking objects, and is very low-power. These are critical attributes for automobile manufacturers processing the large amounts of video required for ADAS and AV applications. We look forward to working with this world-class automobile manufacturer in applying our technology to meet its requirements.”