Abstract: A system and method for customization of software applications with neural network-based features is disclosed. The system acquires information related to one or more functional components of an electronic device and usage data associated with the electronic device. The system selects a computer vision task, based on the acquired information and the usage data, and determines constraints associated with an implementation of the selected computer vision task on the electronic device. The system selects a first neural network as a seed model for the selected computer vision task and execute operations, including a neural architecture search with the seed model and the constraints as input, to obtain a second neural network which is trained on the selected computer vision task. The system updates a software application on the electronic device to include an end-user feature that implements the second neural network for the selected computer vision task.

Abstract: A system collects first data associated with user. The first data includes historical health data and set of sensor data corresponding to a set of health-monitoring parameters. The system applies first Artificial Intelligence (AI) model on the first data to compute indicators which reflect a deviation in a health condition of the user with respect to reference values. Based on the indicators, the system generates first inference data comprising labels or tags associated with a cause of the deviation. Based on the first inference data, the system determines a first requirement for which the user is required to visit a first healthcare center. The system further determines a first set of user-related data associated with the first requirement, based on the first data and the first inference data. Thereafter, the system transfers the first set of user-related data to an electronic healthcare system associated with the first healthcare center.