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.
IBM recently announced they are shutting down IBM Visual Inspection, their product for creating custom computer vision models for classification and object detection. No new instances can be created and
Missed the event or looking for the recording? Check out the Roboflow + Paperspace Detectron2 webinar recording here and notebook here!Tomorrow, Roboflow and Paperspace are co-hosting a webinar teaching you
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.
Computer vision is a generational technology. Like the PC, internet, and mobile phones, computer vision’s impact will reshape every industry. In transportation, for example, the advent of machine vision
Roboflow co-founder Brad Dwyer was a guest on the Software Engineering Daily podcast. Listen on your favorite podcast app (Apple Podcasts, Spotify, Overcast, Stitcher), or see the full transcript below.
Recently, Roboflow machine learning engineer Jacob Solawetz sat down with Elisha Odemakinde, an ML researcher and Community Manager at Data Science Nigeria, for a Fireside chat. During the conversation, Jacob
Roboflow is enabling any developer to use computer vision (without being a machine learning expert). Computer vision is the first technology that fundamentally allows us to rewrite human-computer interaction. Until
This guide will take you the long distance from unlabeled images to a working computer vision model deployed and inferencing live at 15FPS on the affordable and scalable Luxonis OpenCV AI Kit (OAK) device.
We appreciate the machine learning community's feedback, and we're publishing additional details on our methodology.(Note: On June 14, we've incorporated updates from YOLOv4 author Alexey Bochkovskiy, YOLOv5 author Glenn