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insight - Emotion Analysis
顔表情、バレンス・アロウザル、感情強度予測を含む第6回ABAW競争におけるHSEmotion Teamの取り組み
事前学習された深層学習モデルを活用し、顔画像から信頼できる感情特徴を抽出することで、感情分析タスクの精度を大幅に向上させることができる。
Multimodal Emotion Cause Analysis at SemEval 2024 Task 3
The author presents a two-step framework for multimodal emotion cause analysis, utilizing LLMs and GPT models to address challenges in capturing emotions in human conversations.
The 6th Affective Behavior Analysis in-the-wild (ABAW) Competition Overview
The author presents the 6th ABAW Competition focusing on understanding human emotions and behaviors through five challenges, emphasizing the importance of human-centered technologies.
Analyzing Emotions in Low and Moderate Resource Languages
The author explores methods for transferring emotions from resource-rich languages to low-resource languages, focusing on annotation projection and direct cross-lingual transfer. The study aims to improve emotion classification in low and moderate resource languages.
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