Roboflow is a tool for building robust machine learning operations pipelines for
computer vision: from collecting and organizing images, annotating, training,
deploying, and creating active learning [https://blog.roboflow.com/
In this blog, we discuss how to train and deploy a custom license plate detection model to the NVIDIA Jetson. While we focus on the detection of license plates in particular, this guide also provides an end-to-end guide on deploying custom computer vision models to your NVIDIA Jetson on the edge.
Featuring rock, paper, scissors.
OpenAI's CLIP model [https://models.roboflow.com/classification/clip]
(Contrastive Language-Image Pre-Training) is a powerful zero-shot classifier
that leverages knowledge of the English language to classify
Object detection research is white hot! In the last year alone, we've seen the state of the art reached by YOLOv4, YOLOv5, PP-YOLO, and Scaled-YOLOv4. And now Baidu releases PP-YOLOv2, setting new heights in the object detection space.
Using transfer learning
[https://blog.roboflow.com/a-primer-on-transfer-learning/] to initialize your
computer vision model from pre-trained weights rather than starting from scratch
(initializing randomly) has been shown to increase performance
When creating a platform on which people can create and share content, there’s
often a question of content moderation
moderation can mean
Machine learning – the software discipline of mapping inputs to outputs without
explicitly programmed relationships – requires substantial computational
resources. Traditionally, this limits where machine learning models can run to
Excitement is building in the artificial intelligence community around MIT's recent release of liquid neural networks. The breakthroughs that Hasani and team have made are incredible. In this post, we will discuss the new liquid neural networks and what they might mean for the vision field.
Transfer learning [https://blog.roboflow.com/what-is-transfer-learning/] is a
machine learning (ML) technique where knowledge gained during training a set of
problems can be used to solve other related problems.
Object detection technology advances with the release of Scaled-YOLOv4. This blog is written to help you apply Scaled-YOLOv4 to your custom object detection task, to detect any object in the world, given the right training data.
Machine learning algorithms are exceptionally data-hungry, requiring thousands –
if not millions – of examples to make informed decisions. Providing high quality
training data for our algorithms to learn is an expensive