Front Cover: A Memristor-Based In-Memory Computing System-on-Chip with Efficient Depthwise Convolution (Adv. Intell. Syst. 9/2026)

IF 6.1 Q1 AUTOMATION & CONTROL SYSTEMS

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2026-09-19 DOI:10.1002/aisy.70509

Wenhao Song, Fuxi Cai, Sangsu Park, Zhaoyan Li, Seonghun Lee, Mingyi Rao, Woohyung Choi, Seungin Shin, Yan Zhu, Sujin Chae, Myoungsub Kim, Mingche Wu, Hyejung Choi, Yuan Dao, Jaeyun Yi, Youngman Cho, Seon Yong Cha, Ning Ge, Qiangfei Xia, Soo Gil Kim, Miao Hu, J. Joshua Yang

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Abstract

Human Detection in RRAM

The cover image illustrates human detection using an in-memory computing system-on-chip that monolithically integrates memristor (RRAM) arrays with CMOS. A dedicated depthwise convolution architecture enables efficient visual processing, delivering compact, low-power machine vision for hardware AI accelerators. More details can be found in the Research Article by Soo Gil Kim, Miao Hu, J. Joshua Yang, and co-workers (DOI: 10.1002/aisy.202501225).

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封面：一种基于记忆阻器的高效深度卷积内存计算片上系统。系统。9/2026)

RRAM中的人体检测封面图像说明了使用内存计算片上系统进行人体检测，该系统将记忆电阻（RRAM）阵列与CMOS单片集成。专用深度卷积架构可实现高效的视觉处理，为硬件AI加速器提供紧凑、低功耗的机器视觉。更多细节可以在Soo Gil Kim， Miao Hu， J. Joshua Yang及其同事的研究文章中找到（DOI: 10.1002/aisy.202501225）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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