Abstract: An ambient pressure compensation structure for an ultraviolet difference spectrum gas sensor includes a closed box, an ultraviolet difference spectrum gas sensor, a digital pressure sensor, a thermostatic controller, an industrial control computer, a pressure regulating assembly and a limiting partition; the pressure regulating assembly and the limiting partition are arranged inside the closed box, the pressure regulating assembly comprises a piston, a regulating rod and a driving motor, the left side of the piston is connected with the regulating rod, the front end of the regulating rod penetrates out of the closed box and is connected with the driving motor, and the piston divides the interior of the closed box into a pressure regulating air chamber and a working air chamber. Also disclosed is an ambient pressure compensation method for an ultraviolet difference spectrum gas sensor.

Abstract: A laparoscopic image smoke removal method based on a generative adversarial network, and belongs to the technical field of computer vision. The method includes: processing a laparoscopic image sample to be processed using a smoke mask segmentation network to acquire a smoke mask image; inputting the laparoscopic image sample to be processed and the smoke mask image into a smoke removal network, and extracting features of the laparoscopic image sample to be processed using a multi-level smoke feature extractor to acquire a light smoke feature vector and a heavy smoke feature vector; and acquiring, according to the light smoke feature vector, the heavy smoke feature vector and the smoke mask image, a smoke-free laparoscopic image by filtering out smoke information and maintaining a laparoscopic image by using a mask shielding effect. The method has the technical effects of robustness and ability of being embedded into a laparoscopic device for use.

Abstract: A laparoscopic image smoke removal method based on a generative adversarial network, and belongs to the technical field of computer vision. The method includes: processing a laparoscopic image sample to be processed using a smoke mask segmentation network to acquire a smoke mask image; inputting the laparoscopic image sample to be processed and the smoke mask image into a smoke removal network, and extracting features of the laparoscopic image sample to be processed using a multi-level smoke feature extractor to acquire a light smoke feature vector and a heavy smoke feature vector; and acquiring, according to the light smoke feature vector, the heavy smoke feature vector and the smoke mask image, a smoke-free laparoscopic image by filtering out smoke information and maintaining a laparoscopic image by using a mask shielding effect. The method has the technical effects of robustness and ability of being embedded into a laparoscopic device for use.