Dongmei Fu

TL;DR: The Pixel-BERT which aligns semantic connection in pixel and text level solves the limitation of task-specific visual representation for vision and language tasks and relieves the cost of bounding box annotations and overcomes the unbalance between semantic labels in visual task and language semantic.

TL;DR: SOHO as discussed by the authors learns to extract comprehensive yet compact image features through a visual dictionary (VD) that facilitates cross-modal understanding by taking a whole image as input, and learns vision-language representation in an end-to-end manner.

TL;DR: In this article, the atmospheric corrosion of carbon steel was monitored by a Fe/Cu type galvanic corrosion sensor for 34 days using a random forest (RF)-based machine learning approach, which demonstrated higher accuracy than artificial neural network (ANN) and support vector regression (SVR) models in predicting instantaneous atmospheric corrosion.

TL;DR: Wang et al. as mentioned in this paper developed an approach to forecast the outdoor atmospheric corrosion rate of low alloy steels and do corrosion-knowledge mining by using a Random Forests algorithm as a mining tool.

TL;DR: This paper proposes a novel Dynamic Graph Convolutional Module (DGCM), which takes into account all relations and construct dynamic graphs to tolerate large variations of human pose and achieves relative gains over state-of-the-art bottom-up methods on COCO keypoints and MPII dataset.