Two images showing the process of turning handwriting into text
Convolutional Neural Network (CNN)

The Writing, Not the Doodles: A handwriting detection AI model for messy paper.

Systems designed to turn handwriting into text typically work best on pages with a consistent layout, such as a single column unbroken by drawings, diagrams, or extraneous symbols. A new system removes that requirement.
A new metod for compressing images and yielding better classification
Convolutional Neural Network (CNN)

What Machines Want to See: An image compressor for more accurate computer vision

Researchers typically downsize images for vision networks to accommodate limited memory and accelerate processing. A new method not only compresses images but yields better classification.
Surgical robots performing different actions
Convolutional Neural Network (CNN)

Medical AI Gets a Grip: An AI System controlled DaVinci surgical robots.

Surgical robots perform millions of delicate operations annually under human control. Now they’re getting ready to operate on their own.
System designed to isolate changes in the pose of a two-dimensional figure
Convolutional Neural Network (CNN)

Motion Mapper: An AI system for automated animations for video game sprites

In some animated games, different characters can perform the same actions — say, walking, jumping, or casting spells. A new system learned from unlabeled data to transfer such motions from one character to another.
Data related to SElf-supERvised (SEER), an image classifier pretrained on unlabeled images
Convolutional Neural Network (CNN)

Pretraining on Uncurated Data: How unlabeled data improved computer vision accuracy.

It’s well established that pretraining a model on a large dataset improves performance on fine-tuned tasks. In sufficient quantity and paired with a big model, even data scraped from the internet at random can contribute to the performance boost.
Taxonomy of deep learning architectures using self-attention for visual recognition and images from the COCO dataset
Convolutional Neural Network (CNN)

Vision Models Get Some Attention: Researchers add self-attention to convolutional neural nets.

Self-attention is a key element in state-of-the-art language models, but it struggles to process images because its memory requirement rises rapidly with the size of the input. New research addresses the issue with a simple twist on a convolutional neural network.
Images generated by a network designed to visualize what goes on in peoples’ brains while they watch Doctor Who
Convolutional Neural Network (CNN)

What the Brain Sees: AI uses brain activity to create images.

What’s creepier than images from the sci-fi TV series Doctor Who? Images generated by a network designed to visualize what goes on in peoples’ brains while they watch Doctor Who.
Data related to DeepCE, a system designed to predict how particular drugs will influence the amounts of RNA
Convolutional Neural Network (CNN)

Old Drugs for New Ailments: AI searches for Covid-19 treatments among existing drugs.

Many medical drugs work by modulating the body’s production of specific proteins. Recent research aimed to predict this activity, enabling researchers to identify drugs that might counteract the effects of Covid-19.
Graphs and data related to ImageNet performance
Convolutional Neural Network (CNN)

ImageNet Performance, No Panacea: ImageNet pretraining won't always improve computer vision.

It’s commonly assumed that models pretrained to achieve high performance on ImageNet will perform better on other visual tasks after fine-tuning. But is it always true? A new study reached surprising conclusions.
Neural Body, a procedure that generates novel views of a single human character, working
Convolutional Neural Network (CNN)

Seeing People From a New Angle: Neural Body is an AI tool for generating 3D images of people.

The University of Hong Kong, and Cornell University to create Neural Body, a procedure that generates novel views of a single human character based on shots from only a few angles.
Graph showing system that examines X-ray images to predict which Covid-19 patients are at greatest risk of decline
Convolutional Neural Network (CNN)

Covid-19 Triage: Computer vision for x-rays helps triage Covid-19 patients.

The pandemic has pushed hospitals to their limits. A new machine learning system could help doctors make sure the most severe cases get timely, appropriate care.
Art pieces with subjective commentary regarding their emotional impact
Convolutional Neural Network (CNN)

How Art Makes AI Feel: How an AI model feels about art.

An automated art critic spells out the emotional impact of images. Led by Panos Achlioptas, researchers at Ecole Polytechnique, King Abdullah University, and Stanford University trained a deep learning system to generate subjective interpretations of art.
Series of images and graphs related to cancer detection
Convolutional Neural Network (CNN)

Shortcut to Cancer Treatment: AI determines breast cancer treatment from H&E stains.

Doctors who treat breast cancer typically use a quick, inexpensive tumor-tissue stain test to diagnose the illness and a slower, more costly one to determine treatment. A new neural network could help doctors to go straight from diagnosis to treatment.
Convolutional Neural Network (CNN)

Pain Points in Black and White: Medical AI system predicts knee pain from Black patients.

A model designed to assess medical patients’ pain levels matched the patients’ own reports better than doctors’ estimates did — when the patients were Black.
Covid Fast Fax operating
Convolutional Neural Network (CNN)

The Fax About Tracking Covid: A deep learning system for sorting critical Covid-19 cases.

A pair of neural networks is helping to prioritize Covid-19 cases for contact tracing. The public health department of California’s Contra Costa County is using deep learning to sort Covid-19 cases reported via the pre-internet technology known as fax.

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