An image recognition system comprising: a first computer which, in operation, detects a recognition target and feature point data from a detection area of image data , using a detection parameter group for setting the detection area and for detecting the feature point data , the recognition target comprising at least one of a pedestrian, a vehicle and an obstacle; a second computer which, in operation, identifies the recognition target by performing pattern matching between dictionary data and the feature point data detected by the first computer; and a communication path between the first computer and the second computer wherein the first computer and the second computer are disposed in separate housings at positions physically separated from each other, the first computer uses a neural network, the detection parameter group consists of parameters (p1, p2, p3, p4, p5, p6) used for detecting the recognition target from the image data , wherein the detection parameter group is included in a recognition parameter group, and is dynamically changed according to the recognition target, and used for image recognition processing of the image data , wherein the recognition parameter group is at least a part of a parameter group that characterizes the recognition target to be recognized, the detection parameter group is at least one of a synapse weight, a function, and a threshold of a neuron configuring the neural network, wherein the synapse weight is one of a plurality of synapse weights, and a configuration of the neural network is changed by setting zero to at least one of the plurality of synapse weights; and the second computer sends the detection parameter group to the first computer via the communication path when the first computer sends the image data to the second computer . a first computer which, in operation, detects a recognition target and feature point data from a detection area of image data , using a detection parameter group for setting the detection area and for detecting the feature point data , the recognition target comprising at least one of a pedestrian, a vehicle and an obstacle; a second computer which, in operation, identifies the recognition target by performing pattern matching between dictionary data and the feature point data detected by the first computer; and a communication path between the first computer and the second computer wherein the first computer and the second computer are disposed in separate housings at positions physically separated from each other, the first computer uses a neural network, the detection parameter group consists of parameters (p1, p2, p3, p4, p5, p6) used for detecting the recognition target from the image data , wherein the detection parameter group is included in a recognition parameter group, and is dynamically changed according to the recognition target, and used for image recognition processing of the image data , wherein the recognition parameter group is at least a part of a parameter group that characterizes the recognition target to be recognized, the detection parameter group is at least one of a synapse weight, a function, and a threshold of a neuron configuring the neural network, wherein the synapse weight is one of a plurality of synapse weights, and a configuration of the neural network is changed by setting zero to at least one of the plurality of synapse weights; and the second computer sends the detection parameter group to the first computer via the communication path when the first computer sends the image data to the second computer . <EOS>