Abstract: The present invention relates to a first device and at least two second devices for performing distributive machine learning and inference in a communication system. Each device comprises a neural network, NN. The NNs are trained distributively in a training phase and may also be activated during the inference phase, so that an amount of data exchange may be reduced in the communication system. During the training phase and the inference phase, the at least two second devices provide activation vectors of output layers of their NNs to the first device. The first device combines those activation vectors to generate an input for its NN. During backpropagation, the first device may split or broadcast an error vector of the input layer of its NN to the at least two second devices. In this way, an arbitrary number of data sources may be handled by the communication system.

Abstract: Method for monitoring individuals in a place equipped with cameras, the method including the steps of: detecting representative characteristics of an individual in a first zone of the place; detecting representative characteristics of an individual in at least a second zone and comparing these representative characteristics with representative characteristics previously stored in order to determine whether the individual detected in the second zone has been detected in other zones; confirming the determination from a topography of the place by checking consistency of a path of the individual from one zone to another and of the time model by comparing temporal detection information on the representative characteristics in the zones. Device for implementing this method.

Abstract: Method for monitoring individuals in a place equipped with cameras, the method including the steps of: detecting representative characteristics of an individual in a first zone of the place; detecting representative characteristics of an individual in at least a second zone and comparing these representative characteristics with representative characteristics previously stored in order to determine whether the individual detected in the second zone has been detected in other zones; confirming the determination from a topography of the place by checking consistency of a path of the individual from one zone to another and of the time model by comparing temporal detection information on the representative characteristics in the zones. Device for implementing this method.