- Published on July 1, 2022
- In AI Features
How does YOLOv6 compare against YOLOv5?
According to the team, MT-YOLOv6 has carried out improvements and optimisations at the algorithmic level like training strategies and network structure and has displayed impressive results in terms of accuracy and speed when tested on COCO datasets.
Image by Analytics India Magazine
- By Shraddha Goled
Computer vision is one of the most buzzing fields of AI. Major companies are dedicating massive amounts of resources to launch the next big thing in this field. One project that has truly stood out in recent years is YOLO – You Only Look Once. Introduced first in 2015 by Joseph Redmon et al via a paper titled, “You Only Look Once: Unified, Real-Time Object Detection,” it is considered a breakthrough in this field.
Over the years, this model has undergone several iterations and advancements. Version 2 was released in 2016 (YOLO9000: Better, Faster, Stronger), followed by YOLOv3 (YOLOv3: An Incremental Improvement) in 2018, YOLOv4 (YOLOv4: Optimal Speed and Accuracy of Object Detection) in April 2020, and YOLOv5 in May 2020.
YOLOv6 was recently introduced by Chinese company
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Shraddha Goled
I am a technology journalist with AIM. I write stories focused on the AI landscape in India and around the world with a special interest in analysing its long term impact on individuals and societies. Reach out to me at shraddha.goled@analyticsindiamag.com.
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