Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Multimodal intelligence: Representation learning, information fusion, and applications
Deep learning methods haverevolutionized speech recognition, image recognition, and
natural language processing since 2010. Each of these tasks involves a single modality in …
natural language processing since 2010. Each of these tasks involves a single modality in …
Multimodal machine learning: A survey and taxonomy
Our experience of the world is multimodal-we see objects, hear sounds, feel texture, smell
odors, and taste flavors. Modality refers to the way in which something happens or is …
odors, and taste flavors. Modality refers to the way in which something happens or is …
Multimodal sentiment analysis based on fusion methods: A survey
Sentiment analysis is an emerging technology that aims to explore people's attitudes toward
an entity. It can be applied in a variety of different fields and scenarios, such as product …
an entity. It can be applied in a variety of different fields and scenarios, such as product …
Expansion-squeeze-excitation fusion network for elderly activity recognition
This work focuses on the task of elderly activity recognition, which is a challenging task due
to the existence of individual actions and human-object interactions in elderly activities …
to the existence of individual actions and human-object interactions in elderly activities …
Multimodal language analysis in the wild: Cmu-mosei dataset and interpretable dynamic fusion graph
Analyzing human multimodal language is an emerging area of research in NLP. Intrinsically
this language is multimodal (heterogeneous), sequential and asynchronous; it consists of …
this language is multimodal (heterogeneous), sequential and asynchronous; it consists of …
Hybrid contrastive learning of tri-modal representation for multimodal sentiment analysis
The wide application of smart devices enables the availability of multimodal data, which can
be utilized in many tasks. In the field of multimodal sentiment analysis, most previous works …
be utilized in many tasks. In the field of multimodal sentiment analysis, most previous works …
Efficient low-rank multimodal fusion with modality-specific factors
Multimodal research is an emerging field of artificial intelligence, and one of the main
research problems in this field is multimodal fusion. The fusion of multimodal data is the …
research problems in this field is multimodal fusion. The fusion of multimodal data is the …
Memory fusion network for multi-view sequential learning
Multi-view sequential learning is a fundamental problem in machine learning dealing with
multi-view sequences. In a multi-view sequence, there exists two forms of interactions …
multi-view sequences. In a multi-view sequence, there exists two forms of interactions …
Words can shift: Dynamically adjusting word representations using nonverbal behaviors
Humans convey their intentions through the usage of both verbal and nonverbal behaviors
during face-to-face communication. Speaker intentions often vary dynamically depending on …
during face-to-face communication. Speaker intentions often vary dynamically depending on …
Found in translation: Learning robust joint representations by cyclic translations between modalities
Multimodal sentiment analysis is a core research area that studies speaker sentiment
expressed from the language, visual, and acoustic modalities. The central challenge in …
expressed from the language, visual, and acoustic modalities. The central challenge in …