Patent attributes
This disclosure describes methods, apparatuses, and systems for network training and testing for evaluating hardware characteristics and for hardware selection. For example, a sensor can capture a dataset, which may be transformed into a plurality of modified datasets to simulate changes to hardware. Each of the plurality of modified datasets may be used to individually train an untrained neural network, thereby producing a plurality of trained neural networks. In order to evaluate the trained neural networks, each neural network can be used to ingest an evaluation dataset to perform a variety of tasks, such as identifying various objects within the dataset. A performance of each neural network can be determined and compared. A performance curve can be determined for each characteristic under review, facilitating a selection of one or more hardware components and/or configurations.