Výsledky vyhledávání - "Kim, JungHun"

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Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning

Autor: Kim, Junghun, Park, Ka Hyun, Yoon, Hoyoung, Kang, U

Given an edge-incomplete graph, how can we accurately find the missing links? The link prediction in edge-incomplete graphs aims to discover the missing relations between entities when their relationships are represented as a graph. Edge-incomplete g

Externí odkaz: http://arxiv.org/abs/2405.11911

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CMSBERT-CLR: Context-driven Modality Shifting BERT with Contrastive Learning for linguistic, visual, acoustic Representations

Autor: Kim, Junghun, Kim, Jihie

Multimodal sentiment analysis has become an increasingly popular research area as the demand for multimodal online content is growing. For multimodal sentiment analysis, words can have different meanings depending on the linguistic context and non-ve

Externí odkaz: http://arxiv.org/abs/2209.07424

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Representation Learning with Graph Neural Networks for Speech Emotion Recognition

Autor: Kim, Junghun, Kim, Jihie

Learning expressive representation is crucial in deep learning. In speech emotion recognition (SER), vacuum regions or noises in the speech interfere with expressive representation learning. However, traditional RNN-based models are susceptible to su

Externí odkaz: http://arxiv.org/abs/2208.09830

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Improving Speech Emotion Recognition Through Focus and Calibration Attention Mechanisms

Autor: Kim, Junghun, An, Yoojin, Kim, Jihie

Attention has become one of the most commonly used mechanisms in deep learning approaches. The attention mechanism can help the system focus more on the feature space's critical regions. For example, high amplitude regions can play an important role

Externí odkaz: http://arxiv.org/abs/2208.10491

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