This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Choosing the right CPU (central processing unit) for your deep learning project can make all the difference in terms of efficiency, speed, and accuracy. In this article, we’ll explore the best CPUs ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...

Deep Learning and Reinforcement Learning are two of the most popular subsets of Artificial intelligence. The AI market was about $120 billion in 2022 and is increasing at a mind-boggling CAGR above 38 ...

1 Department of Computer Science, University of Manitoba, Winnipeg, MB, Canada 2 Department of Computer Science, University of Western Ontario, London, ON, Canada Machine learning techniques for crop ...

Abstract: In this paper we assess the performance of the new MATLAB Deep Learning Processor. It is a hardware architecture meant for FPGA devices which is able to infer Convolutional Neural Networks.

Convert librosa python feature extraction code to MATLAB. Using the MATLAB feature extraction code, translate a Python speech command recognition system to a MATLAB system where Python is not required ...