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However, image retrieval involves massive distance computation. With the increase in image data volume and dimension, distance computation is suffering from huge power consumption and high computational complexity. Despite the remarkable advantages in energy efficiency shown by nonvolatile content addressable memory (nvCAM)\u2010based in\u2010memory search, achieving software\u2010comparable search accuracy remains a critical challenge under the impact of device variations and other nonideal factors. Here, a heterogeneous image retrieval system combining highly parallel in\u2010memory search with a high\u2010precision digital system is reported. Hamming distance (HD) can be calculated in\u2009situ with a few memory read operations on the memristor\u2010based CAM, and several similar images are fetched for further high\u2010precision rerank in the digital system. 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