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Osseous metastasis, or bone metastasis, refers to the spread of cancer cells from their primary site to the bones, often considered by professionals as an indication that cancer has advanced to a level in which it can no longer be cured. As such, early ...

The fashion industry is a significant contributor to global carbon emissions, water consumption, and waste generation. My Ph.D. project explores two approaches to promote sustainability in fashion recommender systems. First, I aim to develop algorithms ...

In this article, we present Sniffer Faster R-CNN++, an efficient camera-LiDAR late fusion network for low complexity and accurate object detection in autonomous driving scenarios. The proposed detection network architecture operates on output candidates ...

The advent of personalized news recommendation has given rise to increasingly complex recommender architectures. Most neural news recommenders rely on user click behavior and typically introduce dedicated user encoders that aggregate the content of ...

This paper presents a theoretical comparison of early and late fusion methods. An initial discussion on the conditions to apply early or late (soft or hard) fusion is introduced. The analysis show that, if large training sets are available, early ...

Before the arrival of the web as a corpus, people detected positive and negative news based on the understanding of the textual content from physical newspaper rather than an automatic identification approach from readily available e-newspapers. Thus, the ...

With the development of deep learning, many solutions have achieved outstanding performance in solving facial recognition problems. Nevertheless, many challenges still stand, such as occluded face or illumination. This paper proposes a late fusion of many ...

There has been growing interest in using deep learning techniques to recognize emotions from speech. However, real-life emotion datasets collected in call centers are relatively rare and small, making the use of deep learning techniques quite ...

Content-based media retrieval relies on multimodal data representations. For videos, these representations mainly focus on the textual, visual, and audio modalities. While the modality representations can be used individually, combining their ...

Anchor enhanced multi-view late fusion clustering has attracted numerous researchers' attention for its high clustering accuracy and promising efficiency. However, in the existing methods, the anchor points are usually generated through sampling or ...

With the increase of multimedia applications, data are often collected from multiple sensors or modalities, encouraging the rapid development of multi-view (also called multi modal) clustering technique. As a representative, late fusion multi-view ...

Automatic recognition of human emotion has a wide range of applications and has always attracted increasing attention. Expressions of human emotions can apparently be identified across different modalities of communication, such as speech, text, mimics, ...

Multi-view clustering (MVC) has been extensively studied to collect multiple source information in recent years. One typical type of MVC methods is based on matrix factorization to effectively perform dimension reduction and clustering. However, the ...

As a representative of multi-view clustering (MVC), late fusion MVC (LF-MVC) algorithm has attracted intensive attention due to its superior clustering accuracy and high computational efficiency. One common assumption adopted by existing LF-MVC ...

Multi-modal sentiment analysis plays an important role for providing better interactive experiences to users. Each modality in multi-modal data can provide different viewpoints or reveal unique aspects of a user’s emotional state. In this work, we use ...

Sophisticated user interaction in the automotive industry is a fast emerging topic. Mid-air gestures and speech already have numerous applications for driver-car interaction. Additionally, multimodal approaches are being developed to leverage the use of ...

Deep neural networks (DNNs) are universal estimators that have achieved state-of-the-art performance in a broad spectrum of classification tasks, opening new perspectives for many applications. One of them is addressing ensemble learning. In this paper, ...

The ever-growing research in computer vision has created new avenues for user interaction. Speech commands and gesture recognition are already being applied in various touch-based inputs. It is, therefore, foreseeable, that the use of multimodal input ...

The combination of MRI images with textual clinical records, has a great potential since the former contains a raw information about study area of the human body, and the latter contains a human integral assessment of the image performed by doctor. In ...

Natural disasters, especially those related to flooding, are global issues that attract a lot of attention in many parts of the world. A series of research ideas focusing on combining heterogeneous data sources to monitor natural disasters have been ...