An inspection device, comprising: an X-ray inspection system configured to perform X-ray inspection on an inspected object to obtain a transmission image; a memory configured to store the transmission image; and a processor configured to: determine a plurality of candidate regions in the transmission image using a trained firearm detection neural network; classify the plurality of candidate regions using the firearm detection neural network to determine whether there is a firearm included in the transmission image; and mark and fuse images of the firearm in various candidate regions to obtain a position of the firearm in a case that the same firearm is included in a plurality of candidate regions; wherein the memory is configured to store sample transmission images of firearms, and the processor is configured to train the firearm detection neural network by the following operations: initializing a convolutional neural network to obtain an initial detection network; and training the initial detection network using the sample transmission images to obtain the firearm detection neural network; and wherein the processor is configured to create a firearm sample image database including the sample transmission images by the following operations: acquiring sample images of firearms; and preprocessing the sample images. an X-ray inspection system configured to perform X-ray inspection on an inspected object to obtain a transmission image; a memory configured to store the transmission image; and a processor configured to: determine a plurality of candidate regions in the transmission image using a trained firearm detection neural network; classify the plurality of candidate regions using the firearm detection neural network to determine whether there is a firearm included in the transmission image; and mark and fuse images of the firearm in various candidate regions to obtain a position of the firearm in a case that the same firearm is included in a plurality of candidate regions; determine a plurality of candidate regions in the transmission image using a trained firearm detection neural network; classify the plurality of candidate regions using the firearm detection neural network to determine whether there is a firearm included in the transmission image; and mark and fuse images of the firearm in various candidate regions to obtain a position of the firearm in a case that the same firearm is included in a plurality of candidate regions; wherein the memory is configured to store sample transmission images of firearms, and the processor is configured to train the firearm detection neural network by the following operations: initializing a convolutional neural network to obtain an initial detection network; and training the initial detection network using the sample transmission images to obtain the firearm detection neural network; and initializing a convolutional neural network to obtain an initial detection network; and training the initial detection network using the sample transmission images to obtain the firearm detection neural network; and wherein the processor is configured to create a firearm sample image database including the sample transmission images by the following operations: acquiring sample images of firearms; and preprocessing the sample images. acquiring sample images of firearms; and preprocessing the sample images. <EOS>