Graphs comparing SimCLR to SimCLRv2
Classification

Fewer Labels, More Learning

Large models pretrained in an unsupervised fashion and then fine-tuned on a smaller corpus of labeled data have achieved spectacular results in natural language processing. New research pushes forward with a similar approach to computer vision.
Animation of the universe
Classification

Planet Hunter

A machine learning model is scouring the cosmos for undiscovered planets. Astronomers from the University of Warwick developed a system that learned to identify faraway worlds in a dataset of thousands of candidates.
Examples of age, gender and race idenitification by face recognition
Classification

Race Recognition

Marketers are using computer vision to parse customers by skin color and other perceived racial characteristics. A number of companies are pitching race classification as a way for businesses to understand the buying habits of different groups.
AI-powered traffic monitoring in an intersection
Classification

Near-Miss Detection

AI is helping avert traffic accidents by assessing the risk of car crashes at specific intersections. MicroTraffic, a Canadian video analytics company, predicts the odds that accidents will occur at intersections that traditional methods overlook.
Graphs and data related to semi-supervised learning
Classification

All Examples Are Not Equal

Semi-supervised learning — a set of training techniques that use a small number of labeled examples and a large number of unlabeled examples — typically treats all unlabeled examples the same way. But some examples are more useful for learning than others.
Images and data related to a t-shirt that tricks a variety of object detection models into failing to spot people
Classification

Hidden in Plain Sight

With the rise of AI-driven surveillance, anonymity is in fashion. Researchers are working on clothing that evades face recognition systems and designed a t-shirt that tricks a variety of object detection models into failing to spot people.
Data related to AI technology capable of spotting birds with sound and sight
Classification

Birdwatching With AI

Neural networks learned to tell one bird from another, enabling scientists to study their behavior in greater detail. Researchers from universities in Europe and Africa trained eural networks to recognize individual birds with up to 90 percent accuracy.
Graphs and data related to language models and image processing
Classification

Transforming Pixels

Language models like Bert, Ernie, and Elmo have achieved spectacular results based on clever pre-training approaches. New research applies some of those Sesame Street lessons into image processing.
Data related to Covid-19 symptoms prediction
Classification

Cats Cured of Covid

Neural networks are famously bad at interpreting input that falls outside the training set’s distribution, so it’s not surprising that some models are certain that cat pictures show symptoms of Covid-19. A new approach won’t mistakenly condemn your feline to a quarantine.
Series of images and videclips related to the smartphone app Tuna Scope
Classification

Grade-AI Sushi

Computer vision is helping sushi lovers enjoy top-quality maguro. Japanese restaurant chain Kura Sushi is using a smartphone app called Tuna Scope to grade its suppliers’ offerings, according to the news outlet The Asahi Shimbun.
Graphs and data related to Ordered Temporal Alignment Module (Otam)
Classification

Less (Video) is More (Examples)

We’d all love to be able to find similar examples of our favorite cat videos. But few of us want to label thousands of similar videos of even the cutest kitties. New research makes headway in video classification when training examples are scarce.
Map of China pointing specific places in red
Classification

AI Against Covid: Progress Report

A new report details the role of AI in China’s effort to fight the coronavirus. Researchers at Synced, a China-based AI publication, describe how nearly 90 machine learning products have contributed to the country’s pandemic response.
Information and data related to Category-based Subspace Attention Network (CSA-Net)
Classification

Which Shoes Go With That Outfit?

Need a wardrobe upgrade? You could ask the fashion mavens at Netflix’s Queer Eye — or you could use a new neural network. Researchers at Amazon propose Category-based Subspace Attention Network (CSA-Net) to predict and retrieve compatible garments and accessories that complement one another.
AI-powered camera spotting a damaged product
Classification

Assembly Line AI

Computer vision has been learning how to spot manufacturing flaws. The pandemic is accelerating that education. Companies like Instrumental and Elementary are making AI-powered cameras that automate the spotting of damaged or badly assembled products on factory assembly lines.
Examples of detection of animals in images using Detection Transformer (DETR).
Classification

Computer Vision Transformed

The transformer architecture that has shaken up natural language processing may replace recurrent layers in object detection networks. A Facebook team led by Nicolas Carion and Francisco Massa simplified object detection pipelines by using transformers, yielding Detection Transformer (DETR).

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