Abstract: An object detection assistant system includes a memory and a processor. The processor is coupled to the memory. The memory stores one or more commands. The processor accesses and executes one or more commands of the memory. One or more commands include inputting a detection result parameter output by an object detection neural network for object detection of an image to an assistant neural network to output a first correction coefficient after processing by the assistant neural network, where the detection result parameter includes object information and a first confidence; inputting the first correction coefficient and detection result parameters to a Bayesian classifier to output a second correction coefficient; and adjusting the first confidence according to the second correction coefficient to obtain second confidence, and the second confidence being taken as the first confidence of the adjusted detection result parameter.

Abstract: A driving assistance system and a driving assistance method are provided. The driving assistance system includes a plurality of image capturing devices, a congestion calculation module, and a determination module. The image capturing devices capture a plurality of regional images of a plurality of road sections of the target lane. The congestion calculation module calculates a plurality of congestion levels corresponding to the road sections according to the regional images. The determination module provides a lane changing message to the vehicle according to the congestion levels.

Abstract: An object orientation identification method and an object orientation identification device are provided. The method is adapted for the object orientation identification device including a wireless signal transceiver. The object orientation identification device and a target object are both in a moving state. The method includes the following. A first signal is continuously transmitted by the wireless signal transceiver. A second signal reflected back from the target object is received by the wireless signal transceiver. Signal pre-processing is performed on the first signal and the second signal to obtain moving information of the target object with respect to the object orientation identification device. The moving information is input into a deep learning model to obtain orientation information of the target object with respect to the object orientation identification device.

Abstract: A smart parking management system and a smart parking management method are provided. The system includes a first smart pole, multiple second smart poles, and a processing device. An image capturing range of the first smart pole covers an entrance of a road section. An image capturing range of each second smart pole covers at least a parking space of the road section. The processing device is communicatively coupled to the first smart pole and the second smart poles. The processing device identifies first vehicle information of a first vehicle entering the road section according to an image stream captured by the first smart pole, obtains a movement trajectory of the first vehicle in the road section based on the first vehicle information and an image stream captured by each second smart pole, and determines where the first vehicle is parked according to the movement trajectory.

Abstract: The application provides a face recognition method and an electronic device using the method. The method includes: obtaining face information from an image frame in a video stream; determining whether a first similarity between pre-registration information and the face information is higher than a first similarity threshold; determining that face recognition is successful if the first similarity is higher than the first similarity threshold, and updating real-time registration information with the face information; and determining that face recognition fails if the first similarity is lower than the first similarity threshold, and then determining whether a second similarity between the real-time registration information and the face information is higher than a second similarity threshold, where the second similarity threshold is higher than the first similarity threshold.

Abstract: A face recognition system and a method for enhancing face recognition are provided. The method includes: receiving a face image and obtaining a feature of the face image from a feature extraction model; registering the face image to set the feature of the face image as a first recognition feature; performing a synthesis operation on the face image according to at least one first adjustment parameter to generate a synthetic image, and obtaining a feature of the synthetic image from the feature extraction model; comparing first recognition feature with the feature of the synthetic image to obtain a feature similarity; comparing the feature similarity with a threshold value to obtain a comparison result; and registering the synthetic image when the comparison result indicates that the feature similarity is less than or equal to the threshold value.

Abstract: A face recognition system, a method for establishing data of face recognition, and a face recognizing method thereof are disclosed. The face recognition system includes an image obtaining device, a facial analysis module, and a feature comparison module. The image obtaining device is used to obtain a registered facial image. The facial analysis module is used to analyze the registered facial image to obtain a registered facial feature, so as to determine a feature threshold of the registered facial feature. The feature comparison module is used to compare the registered facial feature with a facial feature of a plural facial images to register a facial feature of a similar facial image corresponding to more than a similarity threshold as a false-positive facial image feature. Such that the facial analysis module determines a false-positive threshold of the false-positive facial image feature.

Abstract: An object detection system includes an image capture device, a memory, and a processor. The image capture device captures an image. The memory stores an instruction corresponding to an inference engine based on a multi-scale convolutional neural network architecture including a first, a second, and an object detection scale. The processor executes the instruction to: reduce network widths of convolution layers of the second scale; run the inference engine according to the adjusted convolutional neural network architecture to receive the image as an initial input; input a first output generated by the first scale according to the initial input into the second and the object detection scale; input a second output generated by the second scale according to the first output into the object detection scale; generate a final output according to the first and the second output by the object detection scale, to perform object detection on the image.

Abstract: A voice control device includes a user database, a first image capturing module, a voice command module and a management module. The user database stores first user identification data of a first user account. The first image capturing module captures an environmental image. The voice command module is enabled to receive a voice command for controlling the voice control device. The management module is used to detect whether at least one facial image exists in the environmental image, and detect whether the facial image matches with the first user identification data, and when the facial image matches with the first user identification data, the management module logs in the first user account and enables the voice command module.

Abstract: An object detection system includes an image capture device, a memory, and a processor. The image capture device captures an image. The memory stores an instruction corresponding to an inference engine based on a multi-scale convolutional neural network architecture including a first, a second, and an object detection scale. The processor executes the instruction to: reduce network widths of convolution layers of the second scale; run the inference engine according to the adjusted convolutional neural network architecture to receive the image as an initial input; input a first output generated by the first scale according to the initial input into the second and the object detection scale; input a second output generated by the second scale according to the first output into the object detection scale; generate a final output according to the first and the second output by the object detection scale, to perform object detection on the image.

Abstract: A face recognition system, a method for establishing data of face recognition, and a face recognizing method thereof are disclosed. The face recognition system includes an image obtaining device, a facial analysis module, and a feature comparison module. The image obtaining device is used to obtain a registered facial image. The facial analysis module is used to analyze the registered facial image to obtain a registered facial feature, so as to determine a feature threshold of the registered facial feature. The feature comparison module is used to compare the registered facial feature with a facial feature of a plural facial images to register a facial feature of a similar facial image corresponding to more than a similarity threshold as a false-positive facial image feature. Such that the facial analysis module determines a false-positive threshold of the false-positive facial image feature.

Abstract: The application provides a face recognition method and an electronic device using the method. The method includes: obtaining face information from an image frame in a video stream; determining whether a first similarity between pre-registration information and the face information is higher than a first similarity threshold; determining that face recognition is successful if the first similarity is higher than the first similarity threshold, and updating real-time registration information with the face information; and determining that face recognition fails if the first similarity is lower than the first similarity threshold, and then determining whether a second similarity between the real-time registration information and the face information is higher than a second similarity threshold, where the second similarity threshold is higher than the first similarity threshold.

Abstract: A face recognition system and a method for enhancing face recognition are provided. The method includes: receiving a face image and obtaining a feature of the face image from a feature extraction model; registering the face image to set the feature of the face image as a first recognition feature; performing a synthesis operation on the face image according to at least one first adjustment parameter to generate a synthetic image, and obtaining a feature of the synthetic image from the feature extraction model; comparing first recognition feature with the feature of the synthetic image to obtain a feature similarity; comparing the feature similarity with a threshold value to obtain a comparison result; and registering the synthetic image when the comparison result indicates that the feature similarity is less than or equal to the threshold value.

Abstract: A voice control device includes a user database, a first image capturing module, a voice command module and a management module. The user database stores first user identification data of a first user account. The first image capturing module captures an environmental image. The voice command module is enabled to receive a voice command for controlling the voice control device. The management module is used to detect whether at least one facial image exists in the environmental image, and detect whether the facial image matches with the first user identification data, and when the facial image matches with the first user identification data, the management module logs in the first user account and enables the voice command module.

Abstract: An apparatus management method, an apparatus management device and a non-transitory computer readable storage media are disclosed. The apparatus management method includes following steps. Receive user information and an indicated project at a schedule reservation stage. At least one executable item of the indicated project is in executive order. At least one executable item corresponds to at least one preset apparatus. Determine whether at least one selectable schedule corresponding to a reservation record of the at least one preset apparatus exists. Determine whether a first indicator is received when the at least one selectable schedule exists. The first indicator indicates one of the at least one selectable schedule. Adaptively authorize one of the at least one preset apparatus according to a preset time, the user information and the reservation record of the selectable schedule indicated by the first indicator at a schedule execution stage.

Abstract: An electronic device comprises a detecting unit and a processing unit, comprising. The method of adjusting execution state of electronic device comprises: a current environmental condition is detected through the detecting unit to generate a current environmental signal and the current environmental signal is transmitted to the processing unit. A current execution state of the electronic device is read through the processing unit. A step of comparing with a state look-up table of the electronic device is performed to allow the current environmental signal to correspond to a predetermined environmental condition in the state look-up table of the electronic device. It determines whether the current execution state of the electronic device conforms to a predetermined execution state of the predetermined environmental condition. If not, the current execution state of the electronic device is adjusted to allow the current execution state to be the same with the predetermined execution state.

Abstract: An electronic device comprises a detecting unit and a processing unit, comprising. The method of adjusting execution state of electronic device comprises: a current environmental condition is detected through the detecting unit to generate a current environmental signal and the current environmental signal is transmitted to the processing unit. A current execution state of the electronic device is read through the processing unit. A step of comparing with a state look-up table of the electronic device is performed to allow the current environmental signal to correspond to a predetermined environmental condition in the state look-up table of the electronic device. It determines whether the current execution state of the electronic device conforms to a predetermined execution state of the predetermined environmental condition. If not, the current execution state of the electronic device is adjusted to allow the current execution state to be the same with the predetermined execution state.

Abstract: A hanger may be used for supporting a garment. The hanger may include a hook, a medium connected to the hook, a first branch, a second branch, a third branch, and a fourth branch. The first branch may be connected through the medium to the hook and oriented according to a first direction. The second branch may be connected through the medium to the hook and oriented according to a second direction. The third branch may be coplanar with both the first branch and the hook, disposed between the first branch and the hook, connected to the medium, and oriented according to a third direction different from the first direction. The fourth branch may be connected to the medium and oriented according to a fourth direction different from the second direction, wherein the medium may be disposed between the third branch and the fourth branch.

Abstract: A navigation device and a method for processing navigation information thereof are disclosed. The navigation device includes a display unit, a radio data system (RDS) receiver module, and a central processing unit (CPU). The RDS receiving module is used for receiving an RDS signal and providing the RDS data to the CPU. The CPU converts the RDS data into Open TMC protocol information, runs a navigation program to parse the Open TMC protocol information to obtain traffic information, and makes the display unit displays the traffic information.

Abstract: A mobile communication device and a power saving method thereof are provided. The method determines whether to enter a normal mode or a power saving mode according to the moving state of the mobile communication device to achieve the objective of saving power. The timing start function of the mobile communication device is started under the normal mode, and then the mobile communication device starts every a predetermined time to determine whether to switch to a cell according to the signal intensity of cells. The timing start function of the mobile communication device is closed under the power saving mode. If the device is not moved for a long predetermined time under the power saving mode, it returns to the normal mode from the power saving mode.