Artificial Intelligence

This is a data for cosmetics dataset. The International Patent Classification (IPC) is a standardized, hierarchical system used worldwide to categorize the technical content of patents. It is administered by the World Intellectual Property Organization (WIPO). The IPC system breaks down technology into sections, classes, subclasses, and groups, each representing specific technical domains. By assigning IPC codes to patent documents, patent offices and researchers can systematically organize, search, and analyze patent information across various industries and technological fields.

Defect pattern recognition (DPR) of wafer maps is critical for determining the root cause of production defects, which can provide insights for the yield improvement in wafer foundries. During wafer fabrication, several types of defects can be coupled together in a piece of wafer, it is called mixed-type defects DPR. To detect mixed-type defects is much more complicated because the combination of defects may vary a lot, from the type of defects, position, angle, number of defects, etc. Deep learning methods have been a good choice for complex pattern recognition problems.

Medical imaging has become increasingly important in the diagnosis and treatment of oncological patients, particularly in radiotherapy. 

Traditionally, X-ray-based imaging is widely adopted in RT for patient positioning and monitoring before, during, or after the dose delivery.

Endurance running is a popular activity due to its accessibility. However, participation is sometimes prevented by individuals experiencing respiratory problems. Monitoring breathing with body area networks can tackle these issues by tracking respiration during exercise and providing immediate, guiding feedback. Common breathing guidance systems rely on observational data from past breath cycles and consequently inherit disruptively lagging guidance interventions if breathing pattern suddenly change.

Māori enterprises are pivotal to the economic and cultural prosperity of Aotearoa, yet predictive analysis of business outcomes tailored to these enterprises remains underexplored. This research examines the application of recurrent neural networks (RNNs) and transformer architectures to forecast key performance indicators (KPIs) for Māori small and medium-sized enterprises (SMEs).

This dataset is constructed in a study that addresses the gap between text summarization and content readability for diverse Turkish-speaking audiences. It contains paired original texts and corresponding summaries optimized for different readability levels using the YOD (Yeni Okunabilirlik Düzeyi) formula.

Dataset for QoS-aware LLM Routing Experiment.

paper abstract:

This dataset provides a comprehensive collection of various resources, including the results from Computational Fluid Dynamics (CFD) simulations, the associated CFD processing code, and the dataset along with the source code used for training Convolutional Neural Networks (CNNs). Additionally, it includes data generated by genetic algorithms and the corresponding source code for implementing these algorithms.

This dataset is designed for the classification of textual transcriptions of spoken conversations in Shanghai dialect and Mandarin Chinese. It consists of high-quality, manually transcribed texts from natural dialogues, annotated with corresponding language labels (Shanghai dialect: 1, Mandarin: 0). The dataset aims to facilitate research in text-based dialect classification, natural language processing (NLP), and linguistic variation analysis.

This 3DTeethSegX dataset is a benchmark dataset specifically designed for tooth point cloud completion and segmentation tasks. Built upon the publicly available 3DTeethSeg 2022 MICCAI Challenge dataset, it comprises 1,494 pairs of tooth point clouds and their corresponding tooth images from 38 patients. Each pair includes a partial point cloud (2,048 points) and a complete point cloud (16,384 points).