Improving the Accuracy of Genomic Analysis with DeepVariant 1.0
11 hours ago, googleresearch

Posted by Andrew Carroll, Product Lead, and Pi-Chuan Chang, Technical Lead, Google Health Sequencing genomes involves sampling short pieces of the DNA from the ~6 billion pairs of nucleobases — i.e., adenine (A), thymine (T), guanine (G), and cytosine (C) — we inherit from our parents. Genome sequencing is enabled by two key technologies: DNA sequencers (hardware) that "read" relatively small fragments of DNA, and variant callers (software) that combine the reads to identify where and how an ind...

Improving Sparse Training with RigL
2 days ago, googleresearch

Posted by Utku Evci and Pablo Samuel Castro, Research Engineers, Google Research, Montreal Modern deep neural network architectures are often highly redundant [1, 2, 3], making it possible to remove a significant fraction of connections without harming performance. The sparse neural networks that result have been shown to be more parameter and compute efficient compared to dense networks, and, in many cases, can significantly decrease wall clock inference times. By far the most popular method f...

Imitation Learning in the Low-Data Regime
3 days ago, googleresearch

Posted by Robert Dadashi, Research Software Engineer, and Léonard Hussenot, Student Researcher, Google Research Reinforcement Learning (RL) is a paradigm for using trial-and-error to train agents to sequentially make decisions in complex environments, which has had great success in a number of domains, including games, robotics manipulation and chip design. Agents typically aim at maximizing the sum of the reward they collect in an environment, which can be based on a variety of parameters, incl...

The Technology Behind our Recent Improvements in Flood Forecasting
2 weeks ago, googleresearch

Posted by Sella Nevo, Senior Software Engineer, Google Research, Tel Aviv Flooding is the most common natural disaster on the planet, affecting the lives of hundreds of millions of people around the globe and causing around $10 billion in damages each year. Building on our work in previous years, earlier this week we announced some of our recent efforts to improve flood forecasting in India and Bangladesh, expanding coverage to more than 250 million people, and providing unprecedented lead time...

KeyPose: Estimating the 3D Pose of Transparent Objects from Stereo
2 weeks ago, googleresearch

Posted by Kurt Konolige, Software Engineer, Robotics at Google Estimating the position and orientation of 3D objects is one of the core problems in computer vision applications that involve object-level perception, such as augmented reality and robotic manipulation. In these applications, it is important to know the 3D position of objects in the world, either to directly affect them, or to place simulated objects correctly around them. While there has been much research on this topic using machi...

Using Machine Learning to Detect Deficient Coverage in Colonoscopy Screenings
3 weeks ago, googleresearch

Posted by Daniel Freedman and Ehud Rivlin, Research Scientists, Google Health Colorectal cancer (CRC) is a global health problem and the second deadliest cancer in the United States, resulting in an estimated 900K deaths per year. While deadly, CRC can be prevented by removing small precancerous lesions in the colon, called polyps, before they become cancerous. In fact, it is estimated that a 1% increase in the adenoma detection rate (ADR, defined as the fraction of procedures in which a physici...

Scaling Up Fundamental Quantum Chemistry Simulations on Quantum Hardware
3 weeks ago, googleresearch

Posted by Nicholas Rubin and Charles Neill, Research Scientists, Google AI Quantum Accurate computational prediction of chemical processes from the quantum mechanical laws that govern them is a tool that can unlock new frontiers in chemistry, improving a wide variety of industries. Unfortunately, the exact solution of quantum chemical equations for all but the smallest systems remains out of reach for modern classical computers, due to the exponential scaling in the number and statistics of quan...

Axial-DeepLab: Long-Range Modeling in All Layers for Panoptic Segmentation
3 weeks ago, googleresearch

Posted by Huiyu Wang, Student Researcher, and Yukun Zhu, Software Engineer, Google Research The success of convolutional neural networks (CNNs) mainly comes from two properties of convolution: translation equivariance and locality. Translation equivariance, although not exact, ensures that the model functions well for objects at different positions in an image or for images of different sizes. Locality ensures efficient computation, but at the cost of making the modeling of long-range spatial re...

An Analysis of Online Datasets Using Dataset Search (Published, in Part, as a Dataset)
3 weeks ago, googleresearch

Posted by Natasha Noy, Research Scientist; and Omar Benjelloun, Software Engineer, Google Research There are tens of millions of datasets on the web, with content ranging from sensor data and government records, to results of scientific experiments and business reports. Indeed, there are datasets for almost anything one can imagine, be it diets of emperor penguins or where remote workers live. More than two years ago, we undertook an effort to design a search engine that would provide a single e...

Google at ECCV 2020
3 weeks ago, googleresearch

This week, the 16th European Conference on Computer Vision (ECCV2020) begins, a premier forum for the dissemination of research in computer vision and related fields. Being held virtually for the first time this year, Google is proud to be an ECCV2020 Platinum Partner and is excited to share our research with the community with nearly 50 accepted publications, alongside several tutorials and workshops.If you are registered for ECCV this year, please visit our virtual booth in the Platinum Exhibi...

Understanding View Selection for Contrastive Learning
4 weeks ago, googleresearch

Posted by Yonglong Tian, Student Researcher and Chen Sun, Staff Research Scientist, Google Research Most people take for granted the ability to view an object from several different angles, but still recognize that it's the same object— a dog viewed from the front is still a dog when viewed from the side. While people do this naturally, computer scientists need to explicitly enable machines to learn representations that are view-invariant, with the goal of seeking robust data representations tha...

Tackling Open Challenges in Offline Reinforcement Learning
4 weeks ago, googleresearch

Posted by George Tucker and Sergey Levine, Research Scientists, Google Research Over the past several years, there has been a surge of interest in reinforcement learning (RL) driven by its high-profile successes in game playing and robotic control. However, unlike supervised learning methods, which learn from massive datasets that are collected once and then reused, RL algorithms use a trial-and-error feedback loop that requires active interaction during learning, collecting data every time a ne...

Understanding Deep Learning on Controlled Noisy Labels
4 weeks ago, googleresearch

Posted by Lu Jiang, Senior Research Scientist and Weilong Yang, Senior Staff Software Engineer, Google Research The success of deep neural networks depends on access to high-quality labeled training data, as the presence of label errors (label noise) in training data can greatly reduce the accuracy of models on clean test data. Unfortunately, large training datasets almost always contain examples with inaccurate or incorrect labels. This leads to a paradox: on one hand, large datasets are necess...

Language-Agnostic BERT Sentence Embedding
1 month ago, googleresearch

Posted by Yinfei Yang and Fangxiaoyu Feng, Software Engineers, Google Research A multilingual embedding model is a powerful tool that encodes text from different languages into a shared embedding space, enabling it to be applied to a range of downstream tasks, like text classification, clustering, and others, while also leveraging semantic information for language understanding. Existing approaches for generating such embeddings, like LASER or m~USE, rely on parallel data, mapping a sentence fr...

On-device, Real-time Body Pose Tracking with MediaPipe BlazePose
1 month ago, googleresearch

Posted by Valentin Bazarevsky and Ivan Grishchenko, Research Engineers, Google Research Pose estimation from video plays a critical role enabling the overlay of digital content and information on top of the physical world in augmented reality, sign language recognition, full-body gesture control, and even quantifying physical exercises, where it can form the basis for yoga, dance, and fitness applications. Pose estimation for fitness applications is particularly challenging due to the wide varie...

REALM: Integrating Retrieval into Language Representation Models
1 month ago, googleresearch

Posted by Ming-Wei Chang and Kelvin Guu, Research Scientists, Google Research Recent advances in natural language processing have largely built upon the power of unsupervised pre-training, which trains general purpose language representation models using a large amount of text, without human annotations or labels. These pre-trained models, such as BERT and RoBERTa, have been shown to memorize a surprising amount of world knowledge, such as “the birthplace of Francesco Bartolomeo Conti”, “the dev...

A Simulation Suite for Tackling Applied Reinforcement Learning Challenges
1 month ago, googleresearch

Posted by Daniel J. Mankowitz, Research Scientist, DeepMind and Gabriel Dulac-Arnold, Research Scientist, Google Research Reinforcement Learning (RL) has proven to be effective in solving numerous complex problems ranging from Go, StarCraft and Minecraft to robot locomotion and chip design. In each of these cases, a simulator is available or the real environment is quick and inexpensive to access. Yet, there are still considerable challenges to deploying RL to real-world products and systems. Fo...

On-device Supermarket Product Recognition
1 month ago, googleresearch

Posted by Chao Chen, Software Engineer, Google Research One of the greatest challenges faced by users who are visually impaired is identifying packaged foods, both in a grocery store and also in their kitchen cupboard at home. This is because many foods share the same packaging, such as boxes, tins, bottles and jars, and only differ in the text and imagery printed on the label. However, the ubiquity of smart mobile devices provides an opportunity to address such challenges using machine learning...

MediaPipe Iris: Real-time Iris Tracking & Depth Estimation
1 month ago, googleresearch

Posted by Andrey Vakunov and Dmitry Lagun, Research Engineers, Google Research A wide range of real-world applications, including computational photography (e.g., portrait mode and glint reflections) and augmented reality effects (e.g., virtual avatars) rely on estimating eye position by tracking the iris. Once accurate iris tracking is available, we show that it is possible to determine the metric distance from the camera to the user — without the use of a dedicated depth sensor. This, in-turn,...

Live HDR+ and Dual Exposure Controls on Pixel 4 and 4a
1 month ago, googleresearch

Posted by Jiawen Chen and Sam Hasinoff, Software Engineers, Google Research High dynamic range (HDR) imaging is a method for capturing scenes with a wide range of brightness, from deep shadows to bright highlights. On Pixel phones, the engine behind HDR imaging is HDR+ burst photography, which involves capturing a rapid burst of deliberately underexposed images, combining them, and rendering them in a way that preserves detail across the range of tones. Until recently, one challenge with HDR+ wa...

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