Google’s deep learning TensorFlow platform has added Differentiable Graphics Layers with TensorFlow Graphics, a combination of computer graphics and computer vision. Google says TensorFlow Graphics can solve data labeling challenges for complex 3D vision tasks by leveraging a self-supervised training approach.
Microsoft Build 2019 is around the corner. From May 6 to 8, developers and software engineers will fill Seattle’s Washington State Convention Center, where Microsoft is expected to announce updates to Windows, Office 365, its Azure cloud computing platform, and other company platforms and services.
With its improved productivity and accuracy and more personalized experience, AI is revolutionizing medical imaging. According to Signify Research, the world market for AI in medical imaging — comprising software for automated detection, quantification, decision support, and diagnosis — will reach US$2 billion by 2023.
Advanced machine learning techniques and the widespread deployment of surveillance cameras have dramatically improved the efficiency and accuracy of human detection systems in airports, train stations, and other sensitive public places. Is this the end of anonymity?
The Conference on Computer Vision and Pattern Recognition (CVPR) is one of the world’s top computer vision (CV) conferences. CVPR 2019 runs June 15 through June 21 in Long Beach, California, and the list of accepted papers for the prestigious gathering has now been released.
The Conference on Computer Vision and Pattern Recognition (CVPR) announced this week they have accepted 1300 research papers for CVPR 2019, which will be held June 16 – 20 in Long Beach, California. This year’s submission and acceptance totals both set records for the world’s premier computer vision conference, which had never before accepted more than 1000 papers.
This is the first installment of the Synced Lunar New Year Project, a series of interviews with AI experts reflecting on AI development in 2018 and looking ahead to 2019. In this article, Synced chats with Clarifai Founder and CEO Matt Zeiler on recent progress in computer vision and his company’s plans for the future. Founded in New York in 2013, Clarifai produces advanced image recognition systems.
In a new paper Durham University researchers introduce a anomaly detection model, GANomaly, comprising a conditional generative adversarial network that “jointly learns the generation of high-dimensional image space and the inference of latent space.” The process enables the model to perform anomaly detection tasks even in sample-poor environments.
Computers are now excellent at recognizing images of human faces, cats and dogs — but struggle when it comes to detecting continuous actions, for example determining if a character in a video might be “dancing the tango.” Computers also fall short in detecting nuanced expressions of human emotions.