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METHOD FOR WAKING UP DEVICE, AND SYSTEM AND CHIP

Resumen de: EP4804020A1

This application provides a device wake-up method, a system, and a chip. The method may include: processing a captured first image, determining a motion region image in the first image, and determining, by using a level-1 neural network, whether a target object exists in the motion region image; and when it is determined that the target object exists in the motion region image, performing reconfirmation, by using a level-2 neural network cascaded with the level-1 neural network, on a result output by the level-1 neural network. It can be learned that the target object is determined by using the level-1 neural network and the level-2 neural network, so that a false alarm frequency can be reduced, and system power consumption can be reduced.

FUNCTIONAL ACTIVATION-BASED ANALYSIS OF DEEP NEURAL NETWORKS

Nº publicación: EP4802387A1 09/09/2026

Solicitante:

MEDICAL COLLEGE WISCONSIN INC [US]
The Medical College of Wisconsin, Inc.

Resumen de: US20250148285A1

0000 Functional activation-based analysis of deep neural networks uses a structured set of inputs (e.g., input datasets corresponding to different knowledge or datatype domains) are sequentially provided to a pretrained neural network (e.g., according to a block-sequence). The output values for each node in the neural network are recorded and stored as a time-series of layer output values. A statistical analysis of the time-series of layer output values may be fit as a function of the structured set of inputs to generate neural network analysis data that indicate activations of layers within the neural network based on the inputs.