One-Shot Learning Considerations

An interesting area of current research focuses on developing capabilities of smart objects, such as sensors to do complex processing beyond simple data collection, including mechanisms for energy conservation, in lightweight devices. Sensors that are able to perform recognition or clustering of events in situ minimize the communication time between sensors and controlling devices, such as the base station, and thus improve the performance of the entire network at a large-scale. Such capabilities are limited by the complex computation requirements of existing recognition or clustering algorithms, such as highly iterative training, frequent weight adjustments, and an inability to perform data distribution for large-scale processing.