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Ready To Use Development Environment for Intelligent Camera Based on Deep Learning
EagleCAM is an open front camera solution featuring Renesas’ R-Car V3H and R-Car...
Cortica demonstrates at their booth and in-vehicle their unsupervised learning technology using the highly power-efficient CNN IP available in Renesas’ R-Car V3H SoC for premium front cameras, which is also equipped in the R-Car V3M for high-volume NCAP front cameras. Cortica demonstrates excellent detection of objects, whereas the implementation consumes very low power consumption on the scalable Renesas R-Car V3M and R-Car V3H SoCs.
Cartex 4M is based on a Renesas V3M architecture with at least a 100° FOV. It is composed of three kernels: NCAP. NCAP+, and narrow functions. The three kernels utilize most of the Renesas V3M resources with the following distribution: NCAP kernel 35%, NCAP+ 25%, and the remaining 40% can be utilized by Cartica’s narrow function. The NCAP kernel requirements are set to allow full scores in NCAP VRU, C2C, and SA test cases - required for the overall 5 stars rating.
Cartex 4H is based on a Renesas V3H architecture, with at least a 100° FOV. It is composed of four kernels: Base, safety, performance, and adventure. The four kernels utilize most of the Renesas V3H resources. The base kernel requirements are set to allow full score in NCAP VRU, C2C, and SA test cases which is needed for the overall 5 stars rating. In addition to other base functionality such as: ACC/TJP, LCA, HLB, ADB, TFL, and free space.
Cartex 4F is based on a Renesas V3H architecture with at least a 100° FOV. It is composed of two kernels: Base, and fusion. The two kernels utilize most of the Renesas V3H resources The base kernel requirements are set to allow full score in NCAP VRU, C2C, and SA test cases which is needed for the overall 5 stars rating. In addition to other base functionality such as: ACC, LCA, TJP, and Traffic light assist.