This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...

The efficacy of deep residual networks is fundamentally predicated on the identity shortcut connection. While this mechanism effectively mitigates the vanishing gradient problem, it imposes a strictly ...

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...

1. Demonstrate that scientific knowledge applies across multiple scales of size and/or time. Climate impacts, local vs global. Climate change timescales, long term (geologic timescale) to short term ...

Abu Dhabi is accelerating its aim to become a global hub for deep technology, and at the centre of this effort is VentureOne, a government-backed venture builder turning cutting-edge research into ...

Abstract: Significant advancements in deep learning have been made possible by the utilization of large datasets, underscoring the critical importance of copyright protection. Adding meticulously ...

The ongoing revolution in deep learning is reshaping research across many fields, including economics. Its effects are especially clear in solving dynamic economic models. These models often lack ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Monzo has emerged as one of fintech’s standout success stories – a digital bank that now boasts over 12 million customers and a profitable business model. In an industry where many challengers are ...

We are excited to share our first big milestone in solving a grand challenge that has hampered the predictive power of computational chemistry, biochemistry, and materials science for decades. By ...