728x90 반응형 machine learning81 Vehicle Interior Detection (3) ▤ 목차DataData plays a pivotal role in the success of AI-driven solutions, particularly in applications like Socar's vehicle contamination detection project. The quality, quantity, and diversity of data directly influence the performance, accuracy, and reliability of the AI model. In this project, data serves as the foundation for training, validating, and refining the deep learning model, enablin.. 2025. 1. 23. Vehicle Interior Detection (2) ▤ 목차Proof of ConceptResearch and DevelopmentThis section presents the configuration of the project, detailing the data collection strategies, technical methodologies, anticipated outcomes, and a structured implementation plan. The research and development phase is integral to transforming the theoretical concept into a practical, AI-driven solution that addresses the identified challenges effect.. 2025. 1. 22. 2022 LG Uplus AI Ground (1) ▤ 목차ModelingIn this section, we detail the modeling approaches used during the competition, focusing on the development, experimentation, and optimization of two recommendation algorithms: Neural Collaborative Filtering (NCF) and LightGCN.Neural Collaborative Filtering (NCF)NCF PaperNCFMatrix FactorizationOptunaThe Netflix Prize established matrix factorization (MF) as a fundamental technique in.. 2025. 1. 15. 2022 LG Uplus AI Ground (0) ▤ 목차Competition OverviewThe AI competition, hosted by LG U+ and organized by Upstage, focused on leveraging artificial intelligence to enhance content recommendations within the child-centric media platform "아이들나라 (Children's Country)." This platform caters to young children and their families, offering a wide range of content, from engaging character-driven entertainment to educational material.. 2025. 1. 15. 2nd K-AI Manufacturing Competition (3) ▤ 목차Model Evaluation and ResultsLoss Function and Training ProgressLoss Function:The model was trained using the binary cross-entropy loss function, which is well-suited for binary classification tasks. It calculates the divergence between the predicted probabilities and the true labels, guiding the model's optimization.Binary cross-entropy ensures that the model penalizes incorrect predictions .. 2025. 1. 15. 2nd K-AI Manufacturing Competition (2) ▤ 목차Analysis Model DevelopmentAI Analysis Model Selection: GRURecurrent Neural Networks (RNNs) and LSTMsRecurrent Neural Networks (RNNs) are highly effective for sequential data processing due to their ability to capture temporal dependencies. However, traditional RNNs face limitations in retaining long-term dependencies, often suffering from the vanishing gradient problem.To address this, Long .. 2025. 1. 15. 이전 1 2 3 4 ··· 14 다음 728x90 반응형
