Abstract: A method for target detection based on a visible camera, an infrared camera, and a LiDAR is provided. The method designates visible light images, infrared images, and LiDAR point clouds, which are synchronously acquired, as inputs, and generates an input pseudo-point cloud using visible light images and infrared images, to realize alignment of multimodal information in a three-dimensional space and fusion feature extraction. Then the method adopts a cascade strategy to output more accurate target detection results step by step. In the present disclosure, different characteristics of multi-sensors are complemented, which improves and extends traditional target detection algorithms, improves the accuracy and robustness of target detection, and realizes multi-category target detection in a road scene.

Abstract: An image processing method and an image processing apparatus are provided. The method includes: acquiring a first image including an image of a target person and a second image including an image of target clothes; generating, based on image features of the first image and image features of the second image, a target appearance flow feature for representing deformation of the target clothes matching a body of the target person, and generating, based on the target appearance flow feature, a deformed image of the target clothes matching the body; and generating a virtual dress-up image, in which the target person wears the target clothes matching the body, by fusing the deformed image with the first image.

Abstract: An aftertreatment system includes an upstream particulate filter, a decomposition chamber, a decomposition chamber dosing module, a first downstream catalyst member, and a downstream particulate filter. The decomposition chamber is positioned downstream of the upstream particulate filter. The decomposition chamber dosing module is coupled to the decomposition chamber and is configured to provide downstream treatment fluid into the decomposition chamber. The first downstream catalyst member is positioned downstream of the decomposition chamber and comprises a first downstream catalyst substrate configured to facilitate treatment of exhaust gas. The downstream particulate filter positioned downstream of the first downstream catalyst member.

Abstract: The embodiment of the present disclosure provides a deep neural network (DNN)-based multi-target constant false alarm rate (CFAR) detection method. The method includes: obtaining target values to be measured based on radar IF (IF) signals to be detected, the target values to be measured including a measured frequency value and a measured intensity value of the radar IF signals; obtaining peak sequences based on the target values to be measured; generating a target detection result by processing the peak sequences based on a DNN detector, the DNN detector being a machine learning model; generating approximated maximum likelihood estimation (AMLE) of a scale parameter based on an approximated maximum likelihood estimator; generating a false alarm adjustment threshold based on a preset false alarm rate and the AMLE; and generating a constant false alarm detection result by processing the target detection result based on the false alarm adjustment threshold.

Abstract: Systems and methods for controlling and managing ammonia slip are provided. A method includes: receiving, by a controller, data regarding operation of an exhaust aftertreatment system; determining, by the controller, that a condition for ammonia slip is present based on the data regarding operation of the exhaust aftertreatment system; determining, by the controller, that a condition for ammonia storage is present based on the data regarding operation of the exhaust aftertreatment system; and, commanding, by the controller, a heater to activate and warm a component of the exhaust aftertreatment system to reduce the stored amount of ammonia.

Abstract: A method includes determining, by a controller, that a transient event for a hybrid vehicle is occurring; determining, by the controller, an increase of power demand for the hybrid vehicle based on the determined transient event; directing, by the controller, an amount of power from an electric motor of the hybrid vehicle to a powertrain of the hybrid vehicle based on the increase in power demand, the amount of power from the electric motor determined based on at least one of a state of charge of a battery of the hybrid vehicle; and increasing, by the controller, an amount of power from an engine of the hybrid vehicle as a power output from the electric motor decays to avoid an engine power output spike from the engine based on the determined increase in power demand.

Abstract: The embodiment of the present disclosure provides a deep neural network (DNN)-based multi-target constant false alarm rate (CFAR) detection method. The method includes: obtaining target values to be measured based on radar IF (IF) signals to be detected, the target values to be measured including a measured frequency value and a measured intensity value of the radar IF signals; obtaining peak sequences based on the target values to be measured; generating a target detection result by processing the peak sequences based on a DNN detector, the DNN detector being a machine learning model; generating approximated maximum likelihood estimation (AMLE) of a scale parameter based on an approximated maximum likelihood estimator; generating a false alarm adjustment threshold based on a preset false alarm rate and the AMLE; and generating a constant false alarm detection result by processing the target detection result based on the false alarm adjustment threshold.

Abstract: Methods, apparatuses, and systems for managing a multiple, and particularly a dual-selective catalyst reduction (SCR), exhaust aftertreatment system according to one or more determined reductant dosing strategies are disclosed. A method includes: receiving, by a controller, data indicative of a catalyst of an aftertreatment system; determining, by the controller, a reductant dosing strategy based on a comparison of the data indicative of the catalyst to a respective threshold; and commanding, by the controller, an amount of reductant dosing based on the determined reductant dosing strategy.

Abstract: The present disclosure provides a method for preparing a supported metal alloy catalyst for low temperature engine exhaust oxidation without CO or NO inhibition. The catalyst includes bimetallic PdCu alloy deposited on a SiO2 support using the strong electrostatic adsorption method. The PdCu catalyst may be combined with a traditional PGM-based automotive oxidation catalyst in a series or dual-bed configuration. The first stage of the dual-bed system includes the PdCu catalyst, with the primary role of oxidizing CO at low temperature; the PGM-based catalyst in the second stage then oxidizes NO and hydrocarbons in the absence of any CO-inhibition effects.

Abstract: Disclosed is a multitarget constant false alarm rate detection method based on the signal proxy, which belongs to the technical field of radar constant false alarm rate detection. The method realizes target detection by utilizing the correlation between linear measurements of the radar intermediate frequency signal and the sensing matrix. To achieve a desired false alarm rate, the method determines the threshold by estimating the distributed parameters of the reduced sample set obtained by removing the detected targets from the original sample set. The method provided by the present disclosure can adapt to the sparsity of the signals, realize target detection without relying on the pre-estimated environmental background level, and effectively mitigate the multitarget shadowing effect.

Abstract: A regional oximetry system comprises a pod having a pod housing defining a sensor end and an opposite monitor end. A dual sensor connector is in electrical communication with the sensor end of the pod housing. A monitor connector is in electrical communication with the monitor end of the pod housing. An analog board is disposed within the pod housing and is in electrical communications with the dual sensor connector. The analog board receives and digitizes sensor signals from at least one optical sensor plugged into the dual sensor connector. A digital board is disposed within the pod housing and in electrical communications with the analog board and the monitor connector.