Recognizing actions performed in a video requires understanding each frame and relationships between the frames. Previous research devised a way to analyze individual images efficiently known as Active Shift Layer (ASL). New research extends this technique to the steady march of video frames.
Recognizing actions performed in a video requires understanding each frame and relationships between the frames. Previous research devised a way to analyze individual images efficiently known as Active Shift Layer (ASL). New research extends this technique to the steady march of video frames.
Convolutional neural networks are good at recognizing disease symptoms in medical scans of patients who were injected with iodine-based dye, that makes their organs more visible. But some patients can’t take the dye. Now synthetic scans from a GAN are helping CNNs learn to analyze undyed images.
Convolutional neural networks are good at recognizing disease symptoms in medical scans of patients who were injected with iodine-based dye, that makes their organs more visible. But some patients can’t take the dye. Now synthetic scans from a GAN are helping CNNs learn to analyze undyed images.
New research teaches robots to anticipate what’s coming rather than focusing on what’s right in front of them. Researchers developed Occupancy Anticipation (OA), a navigation system that predicts unseen obstacles in addition to observing those in its field of view.
New research teaches robots to anticipate what’s coming rather than focusing on what’s right in front of them. Researchers developed Occupancy Anticipation (OA), a navigation system that predicts unseen obstacles in addition to observing those in its field of view.
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.
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.
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.
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.
The technique known as dropout discourages neural networks from overfitting by deterring them from reliance on particular features. A new approach reorganizes the process to run efficiently on the chips that typically run neural network calculations.
The White House called for new funding for AI research including a constellation of research centers. Nonetheless, the U.S. government’s annual spending on the technology still would lag behind that of several other...
The White House called for new funding for AI research including a constellation of research centers. Nonetheless, the U.S. government’s annual spending on the technology still would lag behind that of several other...
The technique known as dropout discourages neural networks from overfitting by deterring them from reliance on particular features. A new approach reorganizes the process to run efficiently on the chips that typically run neural network calculations.
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.
Stay updated with weekly AI News and Insights delivered to your inbox