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This paper presents a single-chip, high-performance, and energy-efficient stereo vision depth-estimation processor for micro aerial vehicles (MAVs). The proposed processor implements the state-of-the-art semi-global matching (SGM) algorithm to deliver full high-definition (HD, 1920 ${\times }$ 1080) stereo-depth outputs with a maximum of 38 frames/s throughput. Algorithm-architecture co-optimization...
Conventionally, SRAM PUFs are only used for chip ID. The proposed sequence dependent PUF expands the challenge-response space of an SRAM PUF by an order of rows(sequence length-1), making it suitable for authentication. In addition, it has a sequence dependent non-linear behavior making it more immune to machine learning attacks. In 28nm, the 64×64 SRAM-based PUF has a bit area of 388F2 with energy...
Precise depth estimation is a key kernel function to realizing autonomous navigation on micro-aerial vehicles (MAVs). The state-of-the-art semi-global matching (SGM) algorithm has become favored for its high accuracy. In particular, it effectively handles low texture regions due to its global optimization of the disparity between a left and right image over the entire frame. However, SGM involves...
Security is a key concern in today's mobile devices and a number of hardware implementations of security primitives have been proposed, including true random number generators, differential power attack avoidance, and chip-ID generators [1-4]. Recently, physically unclonable functions (PUFs) were proposed as a secure method for chip authentication in unsecure environments [5-7]. A PUF is a function...
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