Diagnosis of epileptic seizure neurological condition using EEG signal: a multi-model algorithm by Mosleh Hmoud Al-Adhaileh, Mosleh Hmoud Al-Adhaileh, Sultan Ahmad, Alhasan A. Alharbi, Mohammed Alarfaj, Mohammed Alarfaj, Mukta Dhopeshwarkar, Theyazn H. H. Aldhyani

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Adaptive Multi-Model Fault Diagnosis of Dynamic Systems for Motion Tracking by Annalena Daniels, Tommaso Benciolini, Dirk Wollherr, Marion Leibold

“…For most real-world systems, the exact description of possible faults is unknown, making these faults difficult to detect, and even more difficult to identify. …”
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Improving Transferability of Physical Adversarial Attacks on Object Detectors Through Multi-Model Optimization by Adonisz Dimitriu, Tamás Vilmos Michaletzky, Viktor Remeli

“…Physical adversarial attacks face significant challenges in achieving transferability across different object detection models, especially in real-world conditions. This is primarily due to variations in model architectures, training data, and detection strategies, which can make adversarial examples highly model-specific. …”
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OncoFusion: Multi-Model Approach for Generalized and Ovarian Cancer Detection with Stacked Ensembles by Zaware Sarika, Neharkar Rutuja, Sayyad Ayesha, Patil Aarya, Mulla Salma

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A multi-model approach for distance and angle estimation using a custom-designed tag by Emre Erkan

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A multi-layer perceptron neural network for varied conditional attributes in tabular dispersed data. by Małgorzata Przybyła-Kasperek, Kwabena Frimpong Marfo

“…The paper introduces a novel approach for constructing a global model utilizing multilayer perceptron (MLP) neural networks and dispersed data sources. These dispersed data are independently gathered in various local tables, each potentially containing different objects and attributes, albeit with some shared elements (objects and attributes). …”
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Multi-Maneuvering Target Tracking Based on a Gaussian Process by Ziwen Zhao, Hui Chen

“…Traditional multi-model (MM) methods rely on a predefined set of motion models to describe target maneuvering. …”
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An Adaptive Spatio-Temporal Traffic Flow Prediction Using Self-Attention and Multi-Graph Networks by Basma Alsehaimi, Ohoud Alzamzami, Nahed Alowidi, Manar Ali

“…Traffic flow prediction is a pivotal element in Intelligent Transportation Systems (ITSs) that provides significant opportunities for real-world applications. Capturing complex and dynamic spatio-temporal patterns within traffic data remains a significant challenge for traffic flow prediction. …”
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An Elastic Filtering Algorithm with Visual Perception for Vehicle GNSS Navigation and Positioning by Wenzhuo Ma, Zhe Yue, Zengzeng Lian, Kezhao Li, Chenchen Sun, Mengshuo Zhang

“…To address this, we incorporate a zero-speed constraint to further refine vehicle location data when the vehicle is stationary. This constraint matches the data with the appropriate elastic filtering model. …”
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AgriDeep-net: An advanced deep feature fusion-based technique for enhanced fine-grain image analytics in precision agriculture by Rakesh Chandra Joshi, Radim Burget, Malay Kishore Dutta

“…The framework adeptly manages the hurdles posed by uneven data distribution, intra-class diversity, and the demands of multi-class classification. …”
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A seamless LiDAR/IMU/RTK fused localization method for UAV-Based bridge inspection by A. Liang, Y. Pan, Y. Huo, Q. Li, B. Zhou, Z. Chen

“…In cross-scene situations (when the UAV passes through a bridge arch), the quality of sensor data is evaluated based on an interactive multi-model (IMM), and an adaptive switching mechanism is employed between two localization modes—IMU/RTK mode and IMU/LiDAR mode—ensuring smooth and seamless multi-source fusion localization even in the presence of sensor signal fluctuations. …”
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