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- DepMamba: Progressive Fusion Mamba for Multimodal Depression Detection
In this paper, we propose an audio-visual progressive fusion Mamba for multimodal depression detection, termed DepMamba DepMamba features two core designs: hierarchical contextual modeling and progressive multimodal fusion
- 《DepMamba : Progressive Fusion Mamba for Mutilmodal . . .
本文提出了一种用于多模态抑郁症检测的视听渐进融合 Mamba 方法，称为 DepMamba。 DepMamba 具有两个核心设计： 层次化上下文建模 和 渐进式多模态融合。
- DepMamba: Progressive Fusion Mamba for Multimodal Depression Detection . . .
Depression is a common mental disorder that affects millions of people worldwide Although promising, current multimodal methods hinge on aligned or aggregated
- DepMamba: Progressive Fusion Mamba for Multimodal Depression Detection
In this work, we propose an audio-visual progressive fusion Mamba model for efficient multimodal depression detection, termed DepMamba Specifically, the DepMamba features two core designs: hierarchical contextual modeling and progressive multimodal fusion
- DepMamba : Progressive Fusion Mamba for Mutilmodal Depression Detection
We propose DepMamba, the first multimodal depression detection method based on the Mamba to address the challenges of inefficient long-range temporal modeling and sub-optimal multimodal fusion, which can learn efficient representations through hierarchical modeling and progressive fusion, serving as a foundation for future research in
- 【多模态情绪识别】DepMamba : Progressive Fusion Mamba . . .
在本文中，我们提出了一种用于多模态抑郁症检测的视听渐进融合Mamba模型，称为DepMamba。 DepMamba具有两个核心设计：分层上下文建模和渐进多模态融合。
- DepMamba: Progressive Fusion Mamba for Multimodal . . .
Abstract PointJapanese summary of the article (about several hundred characters) All summary is available on JDreamIII (charged) On J-GLOBAL, this item will be available after more than half a year after the record posted In addtion, medical articles require to login to MyJ-GLOBAL Depression is a common mental
- DepMamba : Progressive Fusion Mamba for Mutilmodal Depression Detection
We propose DepMamba, the first multimodal depression detection method based on the Mamba to address the challenges of inefficient long-range temporal modeling and sub-optimal multimodal fusion, which can learn efficient representations through hierarchical modeling and progressive fusion, serving as a foundation for future research in
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