AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...
Abstract: Accurate in-plane displacement field estimation is a key procedure in planar 2-D particle image velocimetry (PIV). In this article, we propose an end-to-end deep learning-based model, termed ...
Abstract: The provincial transportation carbon emissions (TCEs) in China exhibit spatiotemporal heterogeneous characteristics and have become increasingly unpredictable in recent years. To this end, ...
Deep learning approaches to 3D shape segmentation are typically formulated as a multi-class labeling problem. Existing models are trained for a fixed set of labels, which greatly limits their ...
Researchers from Samsung Electronic Co. Ltd. have created a tiny artificial intelligence model that punches far above its weight on certain kinds of “reasoning” tasks, challenging the industry’s ...
Blockchain development firm Recursive introduced the Omni Network, a cross-rollup protocol built on the Ethereum restaking project Eigen Layer. The Omni network aims to be the first generalized ...
While neural networks used in practice are often very deep, the benefit of depth is not well understood. Interestingly, it is known that increasing depth is often harmful for regression tasks. In this ...
Rectified linear unit (ReLU) deep neural network (DNN) is a classical model in deep learning and has achieved great success in many applications. However, this model is characterized by too many ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results