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    Drone Tracking Based on the Fusion of Staring Radar and Camera Data: An Experimental Study by De Rouchechouart, Maxence

    Published 2023
    “…The objective is to assess the benefits of fusing the outputs of both sensors using real data collected during live drone trials. …”
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    Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

    Published 2022
    “…The most important question when using multimodal data is how to fuse them—a field of growing interest among researchers. …”
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    ModeSense: Ubiquitous and Accurate Transportation Mode Detection using Serving Cell Tower Information by Sherif Mostafa (13548916)

    Published 2024
    “…ModeSense introduces a hybrid deep learning-based model that fuses hand-engineered features with automatically extracted features from the serving tower data. …”
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    Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction by Yassine Himeur (14158821)

    Published 2020
    “…This paper presents an efficient non-intrusive load monitoring framework that consists of the following main components: (i) a novel fusion of multiple time-domain features is proposed to extract appliance fingerprints; (ii) a dimensionality reduction scheme is introduced to be applied to the fused time-domain features, which relies on fuzzy-neighbors preserving analysis based QR-decomposition. …”
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    Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering by Saadia Jamil (22045946)

    Published 2024
    “…This raises basic problems like the need for a dimensionality reduction technique for optimal selection of features, fusing the data of different views, and maintaining the inter- and intra-consensus of the multiview dataset. …”
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    Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

    Published 2019
    “…: In multi-modal emotion aware frameworks, it is essential to estimate the emotional features then fuse them to different degrees. This basically follows either a feature-level or decision-level strategy. …”
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    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

    Published 2023
    “…The pre-trained DenseNet201 network is used for CNN feature extraction from each task-specific handwritten image data. The extracted CNN features are then fused in different combinations. …”
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    article
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    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

    Published 2023
    “…The pre-trained DenseNet201 network is used for CNN feature extraction from each task-specific handwritten image data. The extracted CNN features are then fused in different combinations. …”
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    Sensor fusion for real-time condition monitoring of tool wear in surfacing with fly cutters by Ammouri, Ali H.

    Published 2017
    “…As the inputs from these sensors were ‘fused’, the ANN utilized this multiple-sensor data to yield reasonable predictions of ‘good’, ‘used’, and ‘worn’ tools.…”
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    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

    Published 2024
    “…The JPDA (Joint Probability Data Association) with fixed gating and moderate clutter is used in the case of multiple objects. …”
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