Enhanced early detection of dysarthric speech disabilities using stacking ensemble deep learning model by Jagat Chaitanya Prabhala, Ravi Ragoju, Venkatanareshbabu Kuppili, Christophe Chesneau

“…This study introduces Adaptive Dysarthric Speech Disability Detection using Stacked Ensemble Deep Learning (ADSDD-SEDL), an innovative ensemble-based deep-learning framework for dysarthria detection. …”
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Advanced dynamic ensemble framework with explainability driven insights for precision brain tumor classification across datasets by Retinderdeep Singh, Sheifali Gupta, Ashraf Osman Ibrahim, Lubna A. Gabralla, Salil Bharany, Ateeq Ur Rehman, Seada Hussen

“…The proposed system integrates fine-tuned Convolutional Neural Network (CNN), ResNet-50 and EfficientNet-B5 to create a dynamic ensemble framework that addresses existing challenges. …”
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Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices by Muhammad Bisri Musthafa, Samsul Huda, Tuy Tan Nguyen, Yuta Kodera, Yasuyuki Nogami

“…The rapid growth of Internet of Things (IoT) networks has increased security risks, making it essential to have effective Intrusion Detection Systems (IDS) for real-time threat detection. …”
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Multimodal malware classification using proposed ensemble deep neural network framework by Sadia Nazim, Muhammad Mansoor Alam, Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Su’ud

“…Subsequently, the late fusion technique is utilized for multimodal classification by employing Random Under Sampling and Boosting (RUSBoost) and the proposed ensemble deep neural network. The RUSBoost technique involves random undersampling and adaptive boosting to moderate bias toward majority classes while improving minority class (malware) detection. …”
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Optimized Hybrid Deep Learning Framework for Early Detection of Alzheimer’s Disease Using Adaptive Weight Selection by Karim Gasmi, Abdulrahman Alyami, Omer Hamid, Mohamed O. Altaieb, Osama Rezk Shahin, Lassaad Ben Ammar, Hassen Chouaib, Abdulaziz Shehab

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An ensemble learning method with GAN-based sampling and consistency check for anomaly detection of imbalanced data streams with concept drift. by Yansong Liu, Shuang Wang, He Sui, Li Zhu

“…First, we design a comprehensive anomaly detection framework that includes an oversampling module by generative adversarial network, an ensemble classifier, and a consistency check module. …”
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ENHANCING CYBERSECURITY THROUGH MALWARE DETECTION BASED ON MACHINE LEARNING TECHNIQUE by Amer Mohamed Shhatha, Omar Ibrahim Alsaif

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Using a large ensemble of simulations to assess the Northern Hemisphere stratospheric dynamical response to tropical volcanic eruptions and its uncertainty by Matthias Bittner, Hauke Schmidt, Claudia Timmreck, Frank Sienz

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Deconvoluting Protein (Un)folding Structural Ensembles Using X-Ray Scattering, Nuclear Magnetic Resonance Spectroscopy and Molecular Dynamics Simulation. by Alexandr Nasedkin, Moreno Marcellini, Tomasz L Religa, Stefan M Freund, Andreas Menzel, Alan R Fersht, Per Jemth, David van der Spoel, Jan Davidsson

“…Further, the combination of ensemble structural techniques with MD allows for determination of structures and populations of multiple interconverting structures in solution.…”
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Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection. by Islam Zada, Esraa Omran, Salman Jan, Hessa Alfraihi, Seetah Alsalamah, Abdullah Alshahrani, Shaukat Hayat, Nguyen Phi

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Rail Corrugation Detection of High-Speed Railway Using Wheel Dynamic Responses by Jianbo Li, Hongmei Shi

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A novel dynamic weighted prediction framework with stability-enhanced dynamic thresholding feature selection for neurodegenerative disease detection using gait features by Diksha Giri, Ranjit Panigrahi, Samrat Singh Bhandari, Moumita Pramanik, Akash Kumar Bhoi, Victor Hugo C. de Albuquerque

“…Methods A novel ensemble classifier, the Dynamic Weighted Prediction Framework (DWPF), and an innovative feature selection methodology, Stability-Enhanced Dynamic Thresholding (SEDT), have been proposed for neurodegenerative disease detection. …”
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Machine learning based multi-stage intrusion detection system and feature selection ensemble security in cloud assisted vehicular ad hoc networks by C. Christy, A. Nirmala, A. Mary Odilya Teena, A. Isabella Amali

“…MLIDS-RFA has improved detection accuracy (96.2%) and computing efficiency (94.8%) for dynamic VANET management. …”
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BREAST-RANKNet: a fuzzy rank-based ensemble of CNNs with residual learning for enhanced breast cancer detection from ultrasound and mammogram images by Sohaib Asif, Lingying Zhu, Dane Yan, Luman Xu, Zhengqiu Huang, Haimin Xu, Ruxuan Yan, Linghong Cai, Changfu Zheng, Jiamei Lin, Enyu Wang

“…In this paper, we introduce a novel approach, BREAST-RANKNet, designed to overcome existing limitations by employing an adaptive fuzzy rank-based ensemble strategy. This method dynamically combines the decision scores of three state-of-the-art pre-trained CNN models—DenseNet169, MobileNetV1, and InceptionResNetV2—while accounting for the confidence in the predictions of each model. …”
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Dynamic Classifier Auditing by Unsupervised Anomaly Detection Methods: An Application in Packaging Industry Predictive Maintenance by Fernando Mateo, Joan Vila-Francés, Emilio Soria-Olivas, Marcelino Martínez-Sober, Juan Gómez-Sanchis, Antonio José Serrano-López

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Damage Detection and Identification on Elevator Systems Using Deep Learning Algorithms and Multibody Dynamics Models by Josef Koutsoupakis, Dimitrios Giagopoulos, Panagiotis Seventekidis, Georgios Karyofyllas, Amalia Giannakoula

“…High-quality training data are first generated through multibody dynamics simulations and are then combined with healthy state vibration measurements to train an ensemble of autoencoders and convolutional neural networks for damage detection and classification. …”
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Parkinson disease detection based on in-air dynamics feature extraction and selection using machine learning by Jungpil Shin, Abu Saleh Musa Miah, Koki Hirooka, Md. Al Mehedi Hasan, Md. Maniruzzaman

“…To overcome this problem, we proposed an optimized PD detection methodology that incorporates newly developed dynamic kinematic features and machine learning (ML)—based techniques to capture movement dynamics during handwriting tasks. …”
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SE-DeepLabV3+: Cervical Cell Segmentation and Classification Using a Novel SE-Based DeepLabV3+ and Ensemble Method by Betelhem Zewdu Wubineh, Andrzej Rusiecki, Krzysztof Halawa

“…Cervical cancer remains a major cause of morbidity and mortality worldwide, highlighting the need for early detection and effective treatment strategies. This study develops a robust deep learning-based system for cervical cell segmentation and classification using a novel Squeeze-and-Excitation DeepLabV3+ (SE-DeepLabV3+) model with a dynamic atrous rate for segmentation (instead of a fixed dilation rate) and an ensemble method for classification. …”
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DYNAMIC UNBALANCE DETECTION OF CARDAN SHATF IN HIGH-SPEED TRAIN BASED ON MODIFIED VARIATIONAL MODE DECOMPOSITION by HONG JianFeng, DING JianMing, LIN JianHui, ZHENG ShuBin

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DBN-BAAE: Enhanced Lightweight Anomaly Detection Mechanism with Boosting Adversarial Autoencoder by Yanru Chen, Bei Wu, Wang Zhong, Yanru Guo, Dizhi Wu, Yi Ren, Yuanyuan Zhang

“…The proposed lightweight mechanism saves computational overhead, enhances autoencoder training stability with an improved deep belief network (DBN) for pre-training, boosts encoder expression through ensemble learning, achieves high detection accuracy via an adversarial decoder, and employs a dynamic threshold to enhance adaptability and reduce the need for retraining. …”
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