Google Faster R-CNN was developed to improve the speed and accuracy of object detection models. It was based on the original Faster R-CNN architecture introduced by Shaoqing Ren, Kaiming He, Ross B. Girshick, and Jian Sun in 2015. Google later adopted and optimized this model for various applications requiring real-time object detection capabilities.
Google Faster R-CNN
Google Faster R-CNN is a deep learning model designed for object detection tasks. It efficiently identifies and classifies objects within an image, providing bounding boxes around detected items.
Top 5*Generative AI Tools
Howdy Network Rank
#83
Howdy Network Rank#83
Top 5*
43.3%
17.6%
13.1%
11.8%
10.2%
3.9%
Others
*Survey of over 20,000+ Howdy Professionals
The Howdy Network is an international database of 250,000 developers, digital architects, and tech industry professionals. Discover the top 1% of vetted LatAm talent and sort by relevant experience, skills, and tools to find the most qualified candidates.
Explore the Howdy Skills Glossary
About Google Faster R-CNN
How to hire
Hire Google Faster R-CNN Experts
Work with Howdy to gain access to the top 1% of LatAM talent.
Share your Needs
Talk requirements with a Howdy Expert.
Choose Talent
We'll provide a list of the best candidates.
Recruit Risk Free
No hidden fees, no upfront costs, start working within 24 hrs.
How to hire a Google Faster R-CNN expert
A Google Faster R-CNN expert must have skills in deep learning, neural network architecture, Python programming, TensorFlow or PyTorch frameworks, image processing, and experience with object detection algorithms.
USA
$224K
Employer Cost
$127K
Employer Cost
$Howdy savings: $97K
Benefits + Taxes + Fees
Salary
We Save You Money
The best of the best optimized for your budget.
Thanks to our Cost Calculator, you can estimate how much you're saving when hiring top global talent with no middlemen or hidden fees.
*Estimations are based on information from Glassdoor, salary.com and live Howdy data.