Abstract: A method and an apparatus, a device, a vehicle, and a medium for generating a classification model are disclosed. The method for generating a classification model includes (i) acquiring, by a text-image semantic alignment model, a plurality of images associated with a target text, which is indicative of a target scene, (ii) generating an image sample set comprising an image sample labeled with a category by determining which category each of the plurality of images belongs to, and (iii) generating a classification model for the target scene based on the image sample set, wherein the generation of the classification model is based on a pre-trained model utilizing linear probing. In this way, customized classification models can be quickly generated for specific scenes to suit actual needs, providing improved flexibility and accuracy while ensuring the efficiency and stability of the model generation process.

Abstract: An intrusion device having an electromagnetic wave transmitter and receiver with a transmitting and receiving antenna, respectively. The transmitter and receiver may be connected to a microcontroller. The device may operate in a microwave and passive infrared range, and detect speed and position of an intruder, such as an object or a person. The device may be customized to indicate intruders within a certain range of speed and range of distances. Further, the device may have a field of view that may be varied. The device may indicate a direction of movement of the intruder. The transmitter, receiver, controller and antenna may be contained on a compact printed circuit board. Much of the electronics may be incorporated on a monolithic integrated circuit. The customization or adjustment of ranges of speed, slow and fast limits, and distance, near and far limits, may be a reason to regard the device as smart.