Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep-learning software attempts to mimic the activity in layers of neurons in the neocortex, the wrinkly 80 percent of the brain where thinking occurs. The software learns, in a very real sense, to recognize patterns in digital representations of sounds, images, and other data.
Acclivis has dedicated R&D team that works in area of deep learning and artificial intelligence. The team has worked on multiple projects with major automobile company in developing vehicles based on ADAS.
Training on the desired platform for the given set of applications and requirements
Designing consultation in terms of choosing a neural network platform and architecture for client’s target hardware and applications for specific training purposes.
Platform Optimization of neural network path for a number of architectures and platforms to improve performance and power efficiency while retaining its accuracy and predictive capability.
New Model development, deployment and long-term maintenance with respect to client’s requirements for application and hardware platform.
Incremental Updates and Maintenance of neural network as more data becomes available to continuously improve its accuracy. As the target hardware for the network advances, the network’s predictive capabilities can also be upgraded by using additional computer power, expanded memory, and changing power profiles.