Abstract: A sidelink relaying method, a first electronic device, and a non-transitory computer-readable storage medium are closed. The method includes performing, by a first electronic device, a first operation in a relay establishment process for a sidelink based on relay quantity-related information in the sidelink; wherein the first electronic device is an electronic device in the sidelink.

Abstract: Provided are a communication method, a communication apparatus, and a non-transitory computer-readable storage medium. The communication method includes: transmitting or receiving, by a first user equipment UE, a first discovery message; where the first UE is a remote UE, or the first UE is one of multi-hop relay UEs in a topological connection between a remote UE and a network; and the first discovery message includes first identification information and/or hop count information, and the first discovery message is configured to identify UEs in the topological connection.

Abstract: A target cell marking method, including: determining an original image format of the original scanned image, and converting the original scanned image into a first image in a preset image format; segmenting the first image into a plurality of image blocks and recording arrangement positions of the image blocks in the first image; respectively inputting the image blocks into a preset deep learning detection model to obtain first position information of target cells in the image blocks; determining second position information of the target cells in the first image according to the first position information and the corresponding arrangement positions; integrating the image blocks according to the arrangement positions to obtain a second image, and marking the target cells in the second image; and converting the second image marked by the target cells into a third image in the original image format, and displaying the third image.

Abstract: A target cell marking method, including: determining an original image format of the original scanned image, and converting the original scanned image into a first image in a preset image format; segmenting the first image into a plurality of image blocks and recording arrangement positions of the image blocks in the first image; respectively inputting the image blocks into a preset deep learning detection model to obtain first position information of target cells in the image blocks; determining second position information of the target cells in the first image according to the first position information and the corresponding arrangement positions; integrating the image blocks according to the arrangement positions to obtain a second image, and marking the target cells in the second image; and converting the second image marked by the target cells into a third image in the original image format, and displaying the third image.