Cryo-electron microscopy (cryo-EM) has become one of important experimental methods in structure determination. However, despite the rapid growth in the number of deposited cryo-EM maps motivated by advances in microscopy instruments and image processing algorithms, building accurate structure models for cryo-EM maps remains a challenge. Protein secondary structure information, which can be extracted from EM maps, is beneficial for cryo-EM structure modeling. Here, we present a novel secondary structure annotation framework for cryo-EM maps at both intermediate and high resolutions, named EMNUSS. EMNUSS adopts a three-dimensional (3D) nested U-net architecture to assign secondary structures for EM maps. Tested on three diverse datasets including simulated maps, middle resolution experimental maps, and high-resolution experimental maps, EMNUSS demonstrated its accuracy and robustness in identifying the secondary structures for cyro-EM maps of various resolutions. Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-electron microscopy (cryo-EM) maps [1–3]. The'resolution revolution' in cryo-EM has paved the way for the determination of structures of previously intractable biological systems at unprecedented resolution [4–14]. However, the goal of cryo-EM is not to obtain the 3D maps but to determine the detailed atomic structures [15–25]. It is challenging to build accurate structure models for cryo-EM maps [26]. Rigid fitting and flexible fitting are commonly used methods to fit atomic structures into EM maps, but they are only possible if template structures are available. Without template structures, de novo modeling tools are needed to build full-atom models into EM density maps. However, the application of de novo modeling tools is limited because of their precarious accuracy.