How NVIDIA Uses Supervised Learning
7 engineering articles about Supervised Learning from NVIDIA's engineering team
Other NVIDIA Technologies
Articles
Filter:
The article discusses the importance of fine-tuning AI models with synthetic data to enhance multi-camera tracking accuracy. It highlights the use of NVIDIA Isaac Sim and the Omni. Replicator.
Sameer Satish Pusegaonkar
13 min read
Includes Code
Has Summary
--
The article discusses the challenges of training autonomous vehicles (AVs) using real-world data, which is often limited to simple driving scenarios.
Boris Ivanovic
5 min read
Has Summary
--
Project MONAI has made significant advancements with the release of MONAI v0. 8, MONAI Label v0. 3, and MONAI Deploy App SDK v0. 2, along with the introduction of the MONAI Deploy Inference Service.
Michael Zephyr
3 min read
Has Summary
--
The article discusses how to leverage Jupyter Notebooks from the NVIDIA NGC Catalog to accelerate the process of building image segmentation models.
Shokoufeh Monejzi Kouchak
12 min read
Includes Code
Has Summary
--
UC Berkeley's BADGR robot represents a significant advancement in autonomous navigation by utilizing self-supervised learning to navigate complex terrains.
Nefi Alarcon
3 min read
Has Summary
--
NVIDIA Researchers are set to present 19 accepted papers and posters at the CVPR 2018 conference, showcasing advancements in AI and computer vision technologies.
Nefi Alarcon
19 min read
Has Summary
--
NVIDIA showcased its latest AI innovations at NIPS 2017, highlighting research papers, hands-on deep learning labs, and career opportunities in deep learning.
Brad Nemire
2 min read
Has Summary
--
You've reached the end! All 7 articles loaded.