34results about How to "Reduce human judgment" patented technology

The invention discloses a photographing method and a terminal, wherein the method comprises the steps as follows: performing facial recognition to an image in a viewing frame while entering into a photographing mode; calculating the proportion of the face area of a set user in the viewing frame while recognizing the face image of the set user; and photographing while the calculated proportion reaches a set threshold value. The invention further discloses the terminal. According to the invention, the method could be used for performing facial recognition to the image in the viewing frame while entering into the photographing mode; and automatically photographing while the proportion of the recognized face area of the set user in a viewing area reaches the set threshold value to reduce the operation of the user while photographing. The method of the invention could be used for photographing while reaching appropriate proportion that the face area of the user occupying the viewing area so as to reduce the artificial judgment to the image effect while photographing, thereby photographing the user satisfied image.

The invention discloses an anti-interference method of a mobile terminal. The anti-interference method of the mobile terminal comprises the following steps: when the mobile terminal detects an incoming power, judging whether the mobile terminal is currently in an anti-interference mode; when the mobile terminal detects an incoming power, judging whether the mobile terminal is in an anti-interference mode; when the mobile terminal detects an incoming power, judging whether the mobile terminal is in an anti-interference mode. If the mobile terminal starts the anti-interference mode, the incomingcall is intercepted and whether the intercepted call is an interference call is judged based on the preset anti-interference mode; if the intercepted call is an interfering call, the interfering callis automatically blocked. The invention also corresponds to an anti-interference device of a mobile terminal and a readable storage medium. If the terminal intercepts an incoming call, the incoming call information is directly shielded when the incoming call is determined to be an interference incoming call, so that manual judgment of the user is reduced, and the anti-interference mode of the mobile terminal is more intelligent.

The invention discloses a wavelet analysis-based grinding machining working condition detection system and a wavelet analysis-based grinding machining working condition detection method. The system comprises a sensor information acquisition module, a corresponding table module for working conditions and acoustic emission frequency band power, and an intelligent working condition judgment and output module. An acoustic emission sensor is arranged on a grinding machine and transmits acoustic emission signals to the corresponding table module for the working conditions and the acoustic emission frequency band power and the intelligent working condition judgment and output module respectively; the corresponding table module for the working conditions and the acoustic emission frequency band power acquires the standard power intensity of each frequency band by using a wavelet transformation analysis method, and constructs a corresponding table between standard working conditions and standard acoustic emission frequency band power intensity Pst; and the intelligent working condition judgment and output module performs wavelet transformation analysis on the acoustic emission signals to acquire current power intensity, matches the current power intensity with the Pst, calculates a fit error value and determines and outputs a current grinding working condition.

An inspection method and system are disclosed. The method comprises the steps: obtaining a transmission image of inspected cargos; treating the transmission image, to obtain an interest region; and examining the interest region by using a waste detection model, to determine whether the interest region of the transmission image contains waste cargos. By the inspection method and system, human discrimination can be alleviated in a certain extent, the unpacking detecting rate is reduced, and import and export of wastes is facilitated to be safely and fast supervised.

The invention discloses an electric UAV remaining mileage estimation method comprising a step S1 of reading out current battery test data including the electric quantity, voltage and current of a battery through a battery control chip; a step S2 of obtaining electric quantity consumption laws parameters through the battery test data; a step S3 of obtaining laws and parameters between flight states including the flight speed and distance and electric quantity consumption through actual flight data; and a step S4 of calculating a remaining mileage estimated value. The invention can calculate the remaining flight mileage in real time according to the electric quantity of the battery; thus, can reduce human judgment and reduce difficulty in using UAVs; and can automatically calculate the flight distance through an algorithm, and can perform UAV flight operation without multi-user collaboration.

The invention discloses a neural network-based grinding machining working condition detection method, which comprises the following steps of: establishing a neural network model; acquiring field acoustic emission information under a standard working condition by using a sensor information acquisition module, inputting a sample library consisting of the acquired acoustic emission data and standardworking condition data into a neural network learning module, obtaining a weight threshold parameter by using an error back propagation algorithm and outputting the weight threshold parameter to a neural network operation and output module; according to a received real-time data vector, performing an operation and outputting a real-time working condition vector by using the neural network operation and output module; and judging the conditions of a cutter and a work piece according to definitions of each component in the working condition vector. The method has the advantages that: by utilizing a learning and intelligent judgment function of a neural network, the machining conditions of the work piece and the cutter can be automatically judged, dependence on specialized workers is greatlyreduced and machining efficiency is improved, artificial judgment factors can be effectively reduced, machining efficiency and machining quality are improved and unnecessary damages to the work pieceand the cutter are avoided.