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A 118.4 GB/s Multi-Casting Network-on-Chip With Hierarchical Star-Ring Combined Topology for Real-Time Object Recognition

机译：具有分层星环组合拓扑的118.4 GB / s多播片上网络，用于实时目标识别

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Hoi-jun Yoo;
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年度 2014
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1. A 118.4 GB/s Multi-Casting Network-on-Chip With Hierarchical Star-Ring Combined Topology for Real-Time Object Recognition [J] . Kim J.-Y., Park J., Lee S., Solid-State Circuits, IEEE Journal of . 2010,第7期

机译：具有分层星形环组合拓扑的118.4 GB / s多重铸造片上网络，用于实时对象识别
2. Part-based object detection into a hierarchy of image segmentations combining color and topology [J] . Esther Antunez, Rebeca Marfil, Juan P. Bandera, Pattern recognition letters . 2013,第7期

机译：将基于零件的对象检测分解为结合颜色和拓扑的图像分割层次
3. A real-time 3D recognition system by incremental mesh modeling and hierarchical object matching methods [J] . Ryusuke Sagawa, Kei Okada, Satoshi Kagami, 日本ロボット学会誌 . 2002,第1期

机译：通过增量网格建模和分层对象匹配方法的实时3D识别系统
4. A 118.4GB/s Multi-Casting Network-on-Chip for Real-Time Object Recognition Processor [C] . Joo-Young Kim, Kwanho Kim, Seungjin Lee, European Solid-State Circuits Conference . 2009

机译：用于实时对象识别处理器118.4GB / S的多铸造网络
5. Object Recognition in Videos Utilizing Hierarchical and Temporal Objectness with Deep Neural Networks. [D] . Peng, Liang. 2017

机译：利用具有深度神经网络的分层和时间对象性的视频中的对象识别。
6. Representational Content of Oscillatory Brain Activity during Object Recognition: Contrasting Cortical and Deep Neural Network Hierarchies [O] . Leila Reddy, Radoslaw Martin Cichy, Rufin VanRullen 2021

机译：物体识别期间振荡脑活动的代表性含量：对比皮质和深神经网络层次结构
7. A 76.8 GB/s 46 mW Low-latency Network-on-Chip for Real-time Object Recognition Processor [O] . 2014

机译：用于实时物体识别处理器的76.8 GB / s 46 mW低延迟片上网络

A 118.4 GB/s Multi-Casting Network-on-Chip With Hierarchical Star-Ring Combined Topology for Real-Time Object Recognition

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