Disclosed herein are methods and system (101) for training artificial intelligence models (1002) configured to execute image segmentation techniques. The methods and system (101) describe a server (110a) that receives (210) a first image including a set of pixels depicting multiple objects. The server (110a) also receives (230) a second image having a second set of pixels depicting the same set of objects. The server (110a) then analyzes the pixels from the first and second images. When a difference between at least one visual attribute of a pixel within the second image and a corresponding pixel within the first image satisfies a predetermined threshold, it will be encoded as spikes to send to the model, the model (1002) will be trained (250) using supervised STDP rule by revising weights associated with the nodes within the AI model (1002) where the node corresponds to the pixels within the first and/or the second image.
IMAGE CONTOURING USING SPIKING NEURAL NETWORKS