11 skills found
stevehamwu / Emotion Cause Analysis PapersCollection of papers on Emotion Cause Analysis
NUSTM / ChatGPT Sentiment EvaluationCan ChatGPT really understand the opinions, sentiments, and emotions contained in the text? We provide a preliminary evaluation.
NUSTM / MECPE[IEEE TAFFC 2022] Multimodal Emotion-Cause Pair Extraction in Conversations
NUSTM / SemEval 2024 ECAC[SemEval-2024 Task 3] Multimodal Emotion Cause Analysis in Conversations
MIPS-COLT / MER MCEThis paper presents our winning submission to Subtask 2 of SemEval 2024 Task 3 on multimodal emotion cause analysis in conversations.
hanqi-qi / Position Bias Mitigation In Emotion Cause AnalysisACL2021:Position Bias Mitigation: A Knowledge-Aware Graph Model for EmotionCause Extraction
jayusxp / UECA PromptUECA-Prompt: Universal Prompt for Emotion Cause Analysis（COLING 2022）
nicolay-r / THOR ECACThe official fork of THoR Chain-of-Thought framework, enhanced and adapted for Emotion Cause Analysis (ECAC-2024)
NUSTM / MECGC[ACM Multimedia 2024] Observe before Generate: Emotion-Cause aware Video Caption for Multimodal Emotion Cause Generation in Conversations
manjunath5496 / Emotion Cause Analysis Papers"Perhaps the most important principle for the good algorithm designer is to refuse to be content."― Alfred V. Aho
Mehedi-Hasan-Abir / ECG Arrythmia ClassificationElectrocardiogram (ECG) is a painless and noninvasive way to help diagnose many common heart problems in people of all ages. It is a very useful tool for diagnosing any cardiovascular disease such as arrhythmia. Arrhythmia refers to any change in the pattern of ECG signals and also the change of beat rate. That means arrhythmia sums up to most of heart diseases. The beat rate may get faster or slower than the regular. According to the statistics, 80% of sudden cardiac arrest may lead to death [8]. In modern computer science, ECG classification may produce some problems [9]. Feature extraction from the dataset can have lack of good distribution and it may collect temporary feature selection which may causes a bad classification. ECG beats can vary with timing, amplitude of the signals coming from different patients. Each ECG pattern has similar beat shape. Without proper data processing, the classification may give a poor performance. Human emotions can change the heart beat shape such as feeling excited might race the heart beat faster than usual. So, every classification might get some issues regarding the real time data analysis and feature extraction.
