Abstract: A sequence recognition method is implemented by using a sequence recognition network. The sequence recognition network at least includes an encoder network and a decoder network. The method includes: acquiring a to-be-processed image, the to-be-processed image including a to-be-recognized object sequence; encoding the to-be-processed image by using the encoder network to obtain a first feature sequence; decoding the first feature sequence by using the decoder network to obtain a second feature sequence; and obtaining a sequence recognition result of the object sequence based on the second feature sequence, where the sequence recognition network is obtained by respectively supervising the encoder network and the decoder network.

Abstract: Method, apparatuses, systems, electronic devices, computer readable storage media, and computer program products for controlling image acquisition are provided. In one aspect, a method includes: providing a first image sample set to a first neural network; selecting one or more first hard samples from the first image sample set according to a processing result of the first neural network for each first image sample in the first image sample set; determining acquisition environment information of the one or more first hard samples based on the one or more first hard samples; and generating, according to the acquisition environment information, image acquisition control information for instruction of an acquisition of a second image sample set comprising one or more second hard samples.

Abstract: The present disclosure relates to a method and device for recognizing indication information of indicator lights, an electronic apparatus, and a storage medium. The method comprises: acquiring an input image; determining a detection result of a target object based on the input image, the target object including at least one of an indicator light base and an indicator light in a lighted state, and the detection result including a type of the target object and a position of the target region where the target object in the input image is located; and recognizing, based on the detection result of the target object, the target region where the target object in the input image is located to obtain indication information of the target object.

Abstract: A method and device for object detection, and a non-transitory computer readable storage medium are provided. The method includes the following. Object detection is performed on images of at least one second domain with a neural network to obtain detection results, where the neural network is trained with a first image sample set for a first domain. For at least one image among the images of the at least one second domain of which the detection result has a confidence level that is lower than a first threshold, the at least one image is assigned as an image sample in at least one second image sample set. At least one image sample is selected from the first image sample set and at least one image sample is selected from each of the at least one second image sample set.