Do you need to get to the finish line quicker?
At FPGAWorld last month we talked about this and other things to get your final product faster.
So, check our talk again!
Category: Automotive
We have used a neural network for vehicle detection. An SSD network is used to recognize cars, trucks, bicycles and pedestrians in a grey scale environment without impairing speed or accuracy.
CERN, the research faciility in Switzerland and Zenuity, a new ADAS and AD Software Company owned by Volvo and Autoliv, have announced a collaboration on machine learning based on hardware acceleration. This is exactly the area we at BitSims are exploring with our new platform Spiderpig. The idea is utilize existing libraries and the Python language to quickly develop areas such as advanced object recognition and machine learning applications. See here
This announcment from CERN and Zenuity underscores the opportunities we at BitSim see in acceleration of machine learning in hardware. Read further
BitSim is a member of the MIPI Alliance (www.mipi.org), an influential standardization organization within the mobile industry which has successfully developed a number of industry standards for various well-used and established interfaces for camera sensors, displays, storage, power and audio etc.
For some time, a collaboration has been initiated by companies active in the automotive industry, with both car manufacturers and subcontractors to enhance existing or develop new interface specifications for automotive applications.
For short distances in camera applications, MIPI CSI-2 is already used in the automotive industry. BitSim has its own IP block, Bit-MIPI CSI-2, used by customers in different industry segments.
Now, this cooperation will cover solutions for longer distances, up to 15 m, for camera and radar sensors.
Since there will be up to eight cameras in modern cars in the near future, the 40 cm that MIPI CSI-2 can handle today is not enough.
