Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then implement various actions based on the machine’s understanding of images. Georgia Tech is advancing computer vision… Continue reading Georgia Tech Research in Computer Vision – ECCV 2022
Researchers from the Machine Learning Center at Georgia Tech (ML@GT) will present seven papers at the Ninth Annual International Conference on Learning Representations (ICLR). Accepted research will present new findings on topics such as increasing multi-platform deployment and semi-supervised object detection. [RELATED STORY: New Model Defense Strategy Prevents Cloning] ML@GT Associate Director and School of… Continue reading Machine Learning to Present Seven Papers at Prestigious Deep Learning Conference
Researchers from the Machine Learning Center at Georgia Tech (ML@GT) will present eight papers at the 24th International Conference on Artificial Intelligence and Statistics (AISTATS.) One paper by four Georgia Tech researchers, including ML@GT Associate Director Yao Xie, was accepted as an oral presentation, an accomplishment that only 3.1% of more than 1,500 accepted papers… Continue reading Researchers Present Eight Papers at Top Machine Learning and Statistics Conference
With 28 papers to present, the Machine Learning Center at Georgia Tech (ML@GT) is poised to make a big splash at the 2020 Neural Processing and Information Systems (NeurIPS) conference. Adding to the excitement is ML@GT faculty member and Dean of Georgia Tech’s College of Computing, Charles Isbell, will give an invited talk. Isbell’s talk,… Continue reading Isbell to Present Keynote at Premier Neural Processing Conference
Over the years, the Machine Learning Center at Georgia Tech (ML@GT) has steadily been increasing its presence in the natural language processing (NLP) community. With a few new hires this fall and a big performance at this year’s Conference on Empirical Methods in Natural Language Processing (EMNLP), ML@GT is becoming a major player in the field. With 10 papers accepted… Continue reading ML@GT Further Establishes Itself in Natural Language Processing Community
How can someone be persuaded to loan money to a random stranger on the internet? Does the requestor need to be polite or explain the impact the loan would have? Or perhaps they should demonstrate their credibility or use facts to help others understand their need. Does one of these strategies lead to success more… Continue reading Being Polite Can Be Essential to Getting a Loan
Researchers at Georgia Tech are organizing the first ever machine learning and artificial intelligence (AI) cluster at this year’s INFORMS conference. The cluster is being created as INFORMS, one of the major conferences for operations research and analytics, is integrating machine learning more fully into its agenda. Yao Xie and George Lan, associate directors at… Continue reading ML@GT Introduces Machine Learning and AI Cluster at INFORMS Conference
A mathematician by trade, Molei Tao, typically uses mathematics to design algorithms and solve physical science problems like how planets move. Recently, he became attracted to machine learning, an area that according to him, contains numerous interesting problems that are mathematically exciting and can benefit from modern mathematical tools. This year, Tao published his first… Continue reading Tao Wins Best Paper Award at Artificial Intelligence and Statistics Conference
This year’s European Conference on Computer Vision (ECCV) showcases 1,360 papers – 15 of them from the Machine Learning Center at Georgia Tech (ML@GT.) The papers cover a vast array of topics including an idea on how to improve vision and language navigation and a new model that is learning to generate grounded visual captions… Continue reading ML@GT Makes a Strong Showing at Premier European Computer Vision Conference
Annotating and labeling datasets for machine learning problems is an expensive and time-consuming process for computer vision and natural language scientists. However, a new deep learning approach is being used to decode, localize, and reconstruct image and video captions in seconds, making the machine-generated captions more reliable and trustworthy. To solve this problem, researchers at… Continue reading New Algorithm Follows Human Intuition to Make Visual Captioning More Grounded
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