There is provided an electronic device capable of improving the difficulty of breaking a digital electronic lock and the accuracy of gesture control. The electronic device is unlocked according to gestures of a single hand or two hands, an operation hand, a gesture position, a staying time of gesture and a gesture variation of a user. The electronic device further improves the accuracy of gesture control in conjunction with an accessory pattern, temperature sensing and space information of a wearable device. The present disclosure further provides an electronic device that identifies legitimacy of moving the electronic device according to a variation sequence of 3-axis accelerations of an accelerometer.

There is provided a recognition system adaptable to a portable device or a wearable device. The recognition system senses a body heat using a thermal sensor, and performs functions such as the living body recognition, image denoising and body temperature prompting according to detected results.

Disclosed are an operating mode determining method and an operating mode determining device for determining an operating mode of a clothing treatment apparatus using image information by executing an artificial intelligence (AI) algorithm and/or machine learning algorithm in a 5G environment connected for the Internet of Things. According to an embodiment of the present disclosure, the operating mode determining method includes obtaining first image information obtained by photographing clothing through a camera of the clothing treatment apparatus, obtaining second image information obtained by photographing an entrance and exit of a user wearing the clothing through a camera for monitoring an entrance and exit of a room, and determining an operating mode of the clothing treatment apparatus according to an analysis result of the first image information and the second image information.

The present disclosure relates to a visual servoing method based on fusion of distance space and image feature space. The method includes: constructing an image Jacobian matrix; constructing a depth Jacobian matrix; fusing the image Jacobian matrix and the depth Jacobian matrix, to obtain a hybrid visual servoing Jacobian matrix; and obtaining a robot motion control amount according to the hybrid visual servoing Jacobian matrix by using a control algorithm, to enable a robot to move to a target position, to complete precise positioning.

Disclosed is a quaternion multi-degree-of-freedom neuron-based multispectral welding image recognition method, comprising: using three cameras having different wavebands to obtain multispectral weld pool images, and respectively performing pre-processing and edge extraction on the weld pool images having the different wavebands obtained at a same moment by the three cameras; establishing a quaternion-based multispectral weld pool image edge model; extracting low-frequency features after a quaternion discrete cosine transform; using a quaternion-based multi-degree-of-freedom neuron network to perform classification, training and recognition on edge features of the multispectral weld pool images. Compared to traditional means, the present invention has multiple recognition information sources, strong anti-interference capabilities and high recognition accuracy.

There is provided a recognition system adaptable to a portable device or a wearable device. The recognition system senses a body heat using a thermal sensor, and performs functions such as the living body recognition, image denoising and body temperature prompting according to detected results.

According to various embodiments, systems, methods, and mediums for operating an autonomous driving vehicles (ADV) are described. The embodiments use a number of machine learning models to extract features individually from audio data and visual data captured by sensors mounted on the ADV, and then to fuse these extracted features to create a concatenated feature vectors. The concatenated feature vector is provided to a multiplayer perceptron (MLP) as input to generate a detection result related to the presence of an emergency vehicle in the surrounding environment. The detection result can be used by the ADV to take appropriate actions to comply with the local traffic rules.

A control device calculates a first estimate value of a first monitored amount of a mobile object, from sensor information of a controlled object, using a transformed first model obtained by transformation of a first model having a multi-layered neural structure and activation functions of a ReLU structure, and predicting dynamic behavior of the mobile object. The transformed first model is a model for which weight coefficients, biases, and upper and lower limit values of input/output variables of neurons are set based on the first model and in which activation functions of the neurons are transformed using a linear inequality function having a binary variable. The control device calculates a second estimate value of a second monitored amount of the controlled object from a candidate value of an operation amount for controlling the second monitored amount. The control device determines a value of the operation amount based on a target value of the second monitored amount, the second estimate value, and the first estimate value.

An ecological restoration method for a lake wetland against effects of water level rise in a dry season includes: collecting basic data of a lake; determining wetland phytoremediation species of the lake; determining characteristic water levels of the lake under a baseline scenario and under different water level rise scenarios; determining a restoration range based on wetland types corresponding to different characteristic water levels; selecting an experimental restoration area from the restoration range, and performing ecological restoration; and monitoring a plant community state and waterbird biodiversity, judging whether the restoration reaches a preset goal, and adjusting the method if the restoration does not reach the preset goal. According to the method, the effects of water level rise in the dry season on wetland habitat, biodiversity, ecosystem services and the like can be relieved to the greatest extent, so that an ecological restoration effect of the lake wetland is improved.

A system in a vehicle includes an image sensor to obtain images in an image sensor coordinate system and a depth sensor to obtain point clouds in a depth sensor coordinate system. Processing circuitry implements a neural network to determine a validation state of a transformation matrix that transforms the point clouds in the depth sensor coordinate system to transformed point clouds in the image sensor coordinate system. The transformation matrix includes rotation parameters and translation parameters.