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:
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.