A neural network comprises trained interconnected neurons. The neural network is
configured to constrain the relationship between one or more inputs and one or more …

Methods and systems perform incremental learning object detection in images and/or videos
without catastrophic forgetting of previously-learned object classes. A two-stage neural …

A system and method improves the probability of correctly detecting an object from a
collection of source data and reduces the processing load. A plurality of algorithms for a …

A method of training an artificial neural network The artificial neural network comprising a
plurality of connections connecting nodes arranged in at least an initial and a subsequent …

A real-time learning (RTL) neural network is capable of indicating when an input feature
vector is novel with respect to feature vectors contained within its training data set, and is …

A system and method for implementation of attention mechanism in artificial neural
networks, the method com prising: receiving sensor data from at least one sensor sensing …

A system and method for training a neural network that ceases training at or near the
optimally trained point is presented. A neural network having an input layer, a hidden layer …

Prediction and training methods using recurrent neural networks are disclosed. In one
aspect, the prediction method provides a sequence of input data applicable to a plurality of …

To facilitate architecting of a multiple neural network, irrespective of the quantity of cases
and the complexity of case dependence relationship, sets of input instances and the …

A self-organizing neural network having input and output neurons mutually coupled via
bottom-up and top-down adaptive weight matrics performs pattern recognition while using …