GStreamer is a popular open-source framework for creating streaming media applications. Developers often use GStreamer to streamline the development of computer vision and audio perception applications. Since perceptual algorithms are often quite demanding in terms of processing performance, in many […]
Video streams are so rich, and video workloads are so sophisticated, that we may now expect video ML to supply many simultaneous insights and transformations. It will be increasingly common to need video segmentation, object and motion recognition, SLAM, 3D […]
Why did Keurig Dr Pepper—a $12B beverage company—spend years perfecting visual AI technology to recognize the type of beverages consumers are preparing in their Keurig brewers? Does computer vision really yield better coffee? What does it take to make sophisticated […]
Unless you’re a gang member or drug addict, driving is your top risk. But which risks can you handle and which can kill you? Since 96% of collisions are caused by human error and 75% are unconscious (the driver is […]
Eventually, homes will become highly autonomous—powered by ubiquitous, connected, intelligent devices (sometimes referred to as ambient computing)—but this remains a distant vision. In the meantime, advanced presence sensing innovations from component manufacturers, software developers and smart home device companies are […]
Bias is a critical challenge in predictive and generative AI that involves images of humans. People have a variety of body shapes, skin tones and other features that can be challenging to represent completely in training data. Without attention to […]
In this talk, we will explore methods to transform large deep neural network (DNN) models into effective compact models. The transformation process that we focus on—from large to compact DNN form—is referred to as pruning. Pruning involves the removal of […]
An unforeseen change in the input data is called “drift,” and may impact the accuracy of machine learning models. In this talk, we present a novel scheme for diagnosing data drift in the input streams of image classification neural networks. […]
In what format can an AI system best present what it “sees” in a visual scene to help robots accomplish tasks? This question has been a long-standing challenge for computer scientists and robotics engineers. In this presentation, we will provide […]
In this presentation, we will introduce the essential aspects of training convolutional neural networks (CNNs). We’ll discuss the prerequisites for training, including models, data and training frameworks, with an emphasis on the characteristics of data needed for effective training. We […]
