Abstract: Artificial Neural Networks (ANNs) have shown remarkable performance in various fields. However, ANN relies on the von-Neumann architecture, which consumes a lot of power. Hardware-based ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

A great visualization python library used to work with Keras. It uses python's graphviz library to create a presentable graph of the neural network you are building. This library is still unstable.

In Neural Information Processing Systems (NeurIPS) 2018. @inproceedings{yi2018neural, title={Neural-symbolic vqa: Disentangling reasoning from vision and language understanding}, author={Yi, Kexin and ...

Abstract: Neural hardware accelerators have demonstrated notable energy efficiency in tackling tasks, which can be adapted to artificial neural network (ANN) structures. Research is currently directed ...

In this era of pandemic, the future of healthcare industry has never been more exciting. Artificial intelligence and machine learning (AI & ML) present opportunities to develop solutions that cater ...

TensorFlow is an open-source framework developed by Google scientists and engineers for numerical computing. TensorFlow.NET is a library that provides a .NET Standard binding for TensorFlow, allowing ...

See what features you can expect from Azure Machine Learning and IBM Watson to decide which artificial intelligence solution is right for you. With the ability to revolutionize everything from ...