Showing 1 - 5 results of 5 for search 'multiple cloud detection algorithm', query time: 0.15s Refine Results
  1. 1

    A Tutorial on the Use of Artificial Intelligence Tools for Facial Emotion Recognition in R by Austin Wyman (17559054)

    Published 2025
    “…<p>Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. …”
  2. 2

    Aluminum alloy industrial materials defect by Ying Han (20349093)

    Published 2024
    “…<p dir="ltr">The dataset used in this study experiment was from the preliminary competition dataset of the 2018 Guangdong Industrial Intelligent Manufacturing Big Data Intelligent Algorithm Competition organized by Tianchi Feiyue Cloud (https://tianchi.aliyun.com/competition/entrance/231682/introduction). …”
  3. 3

    SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM) by Xiang Cheng (20496924)

    Published 2025
    “…The SynthSoM dataset encompasses multiple data modalities, including radio-frequency (RF) channel large-scale and small-scale fading data, RF millimeter wave (mmWave) radar sensory data, and non-RF sensory data, e.g., RGB images, depth maps, and light detection and ranging (LiDAR) point clouds. …”
  4. 4

    Additional file 1 of The origin and evolution of cultivated rice and genomic signatures of heterosis for yield traits in super-hybrid rice by Yiyong Zhao (21466062)

    Published 2025
    “…GO enrichment analysis results (Q-value < 0.05) for 24,916 genes from 1,383 gene duplications originating from the MRCA of Oryza sativa in Fig. 1, based on 20 genomes using the OmicShare cloud platform ( https://www.omicshare.com/ ). Table S6. …”
  5. 5

    Raw LC-MS/MS and RNA-Seq Mitochondria data by Stefano Martellucci (16284377)

    Published 2025
    “…The centroid of each group, generated by the K-nearest neighbor (KNN) algorithm, was used to define each cluster. All samples from each group were restricted to the same cluster with no overlap.…”