In this work we target the problem of hate speech detection in multimodal publications
formed by a text and an image. We gather and annotate a large scale dataset from Twitter …

End-to-end encryption (E2EE) poses a challenge for automated detection of harmful media,
such as child sexual abuse material and extremist content. The predominant approach at …

Reliable fault detection and diagnostics are crucial in order to ensure efficient operations in
industrial assets. Data-driven solutions have shown great potential in various fields but pose …

A novel intelligent centrifugal pump (CP) fault diagnosis method is proposed in this paper.
The method is based on the contrast in vibration data obtained from a centrifugal pump (CP) …

Social media has become a vital part of humans' day to day life. Different users engage with
social media differently. With the increased usage of social media, many researchers have …

Webly supervised learning has attracted increasing attention for its effectiveness in
exploring publicly accessible data at scale without manual annotation. However, most …

Content-based image retrieval has seen astonishing progress over the past decade,
especially for the task of retrieving images of the same object that is depicted in the query …

This paper presents a machine learning-based classifier for detecting points of interest
through the combined use of images and text from social networks. This model exploits the …

Hashtags are the keywords that describe the theme of social media content and have
become very popular in influence marketing and trending topics. In recent years, hashtag …

Deep quantization methods have shown high efficiency on large-scale image retrieval.
However, current models heavily rely on ground-truth information, hindering the application …