ON FPGA BASED ACCELERATION OF IMAGE PROCESSING IN MOBILE ROBOTICS by Petr Cížek, Jan Faigl

“…The results indicate that even a computationally efficient FAST algorithm can benefit from a parallel (low–cost) FPGA–based implementation that has a competitive processing time but more importantly it is a more power efficient.…”
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A Novel Three-Dimensional Path Planning Method for Fixed-Wing UAV Using Improved Particle Swarm Optimization Algorithm by Chen Huang

“…In the proposed method, the entire path is divided into multiple segments, and these segments are evolved in parallel by using DC strategy, which can convert the complex high-dimensional problem into several parallel low-dimensional problems. In addition, A∗ algorithm is adopted to generated an optimal path from the particle swarm, which can avoid premature convergence and enhance global search ability. …”
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Integrated multi-operand optical neurons for scalable and hardware-efficient deep learning by Feng Chenghao, Gu Jiaqi, Zhu Hanqing, Ning Shupeng, Tang Rongxing, Hlaing May, Midkiff Jason, Jain Sourabh, Pan David Z., Chen Ray T.

“…Optical neural networks (ONNs) are promising hardware platforms for next-generation neuromorphic computing due to their high parallelism, low latency, and low energy consumption. However, previous integrated photonic tensor cores (PTCs) consume numerous single-operand optical modulators for signal and weight encoding, leading to large area costs and high propagation loss to implement large tensor operations. …”
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Design of a discrete сosine transformation processor for image compression systems on a losless-to-lossy circuit by V. V. Kliuchenia

“…At the same time, such characteristics as structural regularity, modularity, high computational parallelism,  low  latency  and  power  consumption  are  taken  into  account.  …”
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