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Found 7 papers, 3 papers with code
Applying Deep Learning to Basketball Trajectories
Using a dataset of over 20, 000 three pointers from NBA SportVu data, the models based simply on sequential positional data outperform a static feature rich machine learning model in predicting whether a three-point shot is successful.
Applying Deep Bidirectional LSTM and Mixture Density Network for Basketball Trajectory Prediction
In the hit-or-miss classification experiment, the proposed model outperformed other models in terms of the convergence speed and accuracy.
Detecting Offensive Tweets in Hindi-English Code-Switched Language
The paper focuses on the classification of offensive tweets written in Hinglish language, which is a portmanteau of the Indic language Hindi with the Roman script.
Identification of Emergency Blood Donation Request on Twitter
Social media-based text mining in healthcare has received special attention in recent times due to the enhanced accessibility of social media sites like Twitter.
Did you offend me? Classification of Offensive Tweets in Hinglish Language
The use of code-switched languages (\textit{e. g.}, Hinglish, which is derived by the blending of Hindi with the English language) is getting much popular on Twitter due to their ease of communication in native languages.
Exploring and Learning Suicidal Ideation Connotations on Social Media with Deep Learning
The increasing suicide rates amongst youth and its high correlation with suicidal ideation expression on social media warrants a deeper investigation into models for the detection of suicidal intent in text such as tweets to enable prevention.
MM-PhyQA: Multimodal Physics Question-Answering With Multi-Image CoT Prompting
While Large Language Models (LLMs) can achieve human-level performance in various tasks, they continue to face challenges when it comes to effectively tackling multi-step physics reasoning tasks.
