With the advent of new technologies such as the Artificial Intelligence of Things (AIoT), big
data, fog computing, and edge computing, smart city applications have suffered from issues …

Image and text matching plays a crucial role in bridging the cross-modal gap between vision
and language, and has achieved great progress due to the deep learning. However, the …

During the last decades, deep learning (DL) has been proven to be a very powerful and
successful technique in many real-world applications, eg, video surveillance or object …

Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living
standards, facilitating the rapid expansion of urban areas while efficiently managing …

Multi-expert networks have shown great superiority for imbalanced data classification tasks
due to their complementary and diverse. We have summarized two aspects for further …

Online intelligent recognition of coal and gangue is an important aspect of coal mine
intelligent development. Current research focuses more on improving recognition accuracy …

Recently, many effective methods have emerged to address the robustness problem of
Deep Neural Networks (DNNs) trained with noisy labels. However, existing work on learning …

Logit adjustment is an effective long-tailed visual recognition strategy to encourage a
significant margin between rare and dominant labels. Existing methods typically employ the …

Imbalanced label distribution is usually the case for real-world data, which poses a
challenge for training unbiased recognition model. In this paper, we study two underlying …

The scene graph generation aims to recognize objects and infer the relationships between
them, which can provide a comprehensive understanding of image visual perception …