This article brings two major contributions. First, we present the results of a critical analysis
of recent scientific articles about neural and non-neural approaches and representations for …

The application of deep learning (DL) for solving construction safety issues has achieved
remarkable results in recent years that are superior to traditional methods. However, there is …

E-commerce platforms are becoming a primary place for people to find, compare and
ultimately purchase products. One of the fundamental questions that arises in e-commerce is …

The text classification task is an important application in natural language processing. At
present, deep learning models, such as convolutional neural network and recurrent neural …

Visual question answering automatically answers natural language questions according to
the content of an image or video. The task is challenging because it requires the …

In the recent trends, the world has stepped into a multimedia era for enhancing business,
recommendation systems, and information retrieval, etc. Multimedia data is highly rich in …

Convolutional neural networks (CNN), recurrent neural networks (RNN), attention, and their
variants are extensively applied in the sentiment analysis, and the effect of fusion model is …

Multi-label text classification task is one of the research hotspots in the field of natural
language processing. However, most of the existing multi-label text classification models are …

Abstract Machine Translation (MT) is one of the challenging tasks in the field of Natural
Language Processing (NLP). The Convolutional Neural Network (CNN)-based approaches …

With continuous development of artificial intelligence, text classification has gradually
changed from a knowledge-based method to a method based on statistics and machine …