A good weight initialization is crucial to accelerate the convergence of the weights in a
neural network. However, training a neural network is still time-consuming, despite recent …

Visual affordance grounding aims to segment all possible interaction regions between
people and objects from an image/video, which benefits many applications, such as robot …

The prediction of ecological toxicity plays an increasingly important role in modern society.
However, the existing models often suffer from poor performance and limited predictive …

Due to the growing emphasis on food safety, peptide research is increasingly focusing on
food sources. Traditional methods for determining peptide properties are expensive. While …

Weather-related phenomena such as clouds, rain, snow affect the performance of radio
links. To reduce the adverse effects of radio link failures' on the user experience, mobile …

We examine named entity recognition (NER), an essential and commonly used first step in
many natural language processing tasks, including chatbots and language translation. We …

Abstract In Aspect-based Sentiment Analysis (ABSA), accurately determining the sentiment
polarity of specific aspects within text requires a nuanced understanding of linguistic …

Online learning of deep neural networks suffers from challenges such as hysteretic non-
incremental updating, increasing memory usage, past retrospective retraining, and …

In this paper, a comprehensive risk assessment system is proposed to evaluate the risk of
collapse in mountain tunnels. This system integrates risk source identification, dynamic and …

The global horizontal irradiance (GHI) is the most important metric for evaluating solar
resources. The accurate prediction of GHI is of great significance for effectively assessing …