In this blog post, we are going to introduce autoencoders
[https://en.wikipedia.org/wiki/Autoencoder], describe the several autoencoder
types that exist, and showcase their applications.
An autoencoder is
You'll hear the words "supervised learning" and "unsupervised learning" a lot in discussions about data science, machine learning, and other related fields. Being able to distinguish between supervised and unsupervised
As Ph.D. students in the Active Robotics Sensing Lab (ARoS) at NC State under the supervision of Dr. Edgar Lobaton, we developed in conjunction with The Engineering Place at NC State a set of activities to walk high school students through the entire computer vision pipeline.
YOLOv5 [https://blog.roboflow.com/yolov5-improvements-and-evaluation/] is one of
the most popular object detection networks in the world, and now object
detection isn't the only trick up its sleeve!
NVIDIA's TAO Toolkit provides a framework for fine-tuning popular computer vision models using your own data. In this tutorial, we'll be demonstrating how to use Roboflow to curate a high-quality computer vision dataset to use with NVIDIA's TAO Toolkit.
Everybody hates installing NVIDIA drivers, you have to manually download them,
then install cuda [https://blog.roboflow.com/what-is-cuda/]
[https://search.brave.com/search?q=cuda&source=desktop], be sure
Benefits to Existing Models
Polygons have traditionally been used for training image segmentation models
polygons can also improve the training of object detection models
TensorFlow Lite [https://www.tensorflow.org/lite], often referred to as TFLite,
is an open source library developed by Google