A Method for Predicting the Remaining Life of Lithium-Ion Batteries Based on an Improved Dempster–Shafer Evidence Theory Framework by Tongrui Zhang, Hao Sun

“…This paper proposes a RUL prediction method for lithium-ion batteries based on an improved Dempster–Shafer (D-S) evidence theory framework, which aims to improve the accuracy and robustness of prediction by integrating the advantages of a wavelet packet decomposition convolutional neural network (WPD-CNN) and an extended Kalman filter (EKF). …”
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An object-based spectral and elevation feature fusion framework for landslide mapping using time-series Landsat-8 imagery by Tsung-Han Wen, Tee-Ann Teo

“…This study presents an object-based spectral and elevation feature fusion framework for landslide mapping using time-series Landsat-8 imagery. …”
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Attention-Enhanced Hybrid Automatic Modulation Classification for Advanced Wireless Communication Systems: A Deep Learning-Transformer Framework by Sam Ansari, Khawla A. Alnajjar, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny, Abir Hussain, Soliman Mahmoud

“…To address these limitations, this paper presents a novel attention-enhanced hybrid AMC framework that synergistically integrates specialized convolutional layers for efficient temporal feature extraction with a compact transformer encoder for global sequence modeling. …”
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An Insight on the Timely Diagnosis of Diabetic Retinopathy Using Traditional and AI-Driven Approaches by Malaika Asif, Fasih Ur Rehman, Zoya Rashid, Altaf Hussain, Alina Mirza, Waqar Shahid Qureshi

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A hybrid optimization-enhanced 1D-ResCNN framework for epileptic spike detection in scalp EEG signals by Priyaranjan Kumar, Prabhat Kumar Upadhyay

“…Abstract In order to detect epileptic spikes, this paper suggests a deep learning architecture that blends 1D residual convolutional neural networks (1D-ResCNN) with a hybrid optimization strategy. …”
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A deep learning framework for gender sensitive speech emotion recognition based on MFCC feature selection and SHAP analysis by Qingqing Hu, Yiran Peng, Zhong Zheng

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A computational framework for IoT security integrating deep learning-based semantic algorithms for real-time threat response by Ripal Ranpara, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-Zahrani

“…The proposed research framework integrates Convolutional Neural Networks for spatial anomaly detection and Recurrent Neural Networks for sequential pattern recognition. …”
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mmHSE: A Two-Stage Framework for Human Skeleton Estimation Using mmWave FMCW Radar Signals by Jiake Tian, Yi Zou, Jiale Lai

“…We present mmHSE, a two-stage framework for human skeleton estimation using dual millimeter-Wave (mmWave) Frequency-Modulated Continuous-Wave (FMCW) radar signals. …”
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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

“…We implement and evaluate this proposed framework on the CICIDS2017 dataset. Experimental results show that our proposed framework outperforms state-of-the-art approaches, vastly improving DL model detection accuracy by 98% using CNN.…”
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A proximal policy optimization based deep reinforcement learning framework for tracking control of a flexible robotic manipulator by Joshi Kumar V, Vinodh Kumar Elumalai

“…The experimental validation on robotic manipulator system through hardware in loop (HIL) testing substantiates that the proposed framework offers faster convergence and better vibration suppression feature compared to the state-of-the-art policy gradient technique and actor-critic technique.…”
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A Residual-Corrected Hybrid ARIMA–CNN–LSTM Framework for High-Accuracy Tobacco Sales Forecasting in Regulated Markets by Shiyu Huang, Lili Zhou

“…In this paper, leveraging 2023 daily sales data from a Southern Chinese tobacco company, this study proposes a new hybrid deep learning framework that integrates ARIMA, CNN, and LSTM models to address these inherent limitations and enhance prediction accuracy. …”
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Deep Learning-Assisted Discovery of Analogy-Inspired Designs within Peter Collins' Analogical Architectural Design Classification Framework by Hüseyin Özdemir

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An interpretable framework for gastric cancer classification using multi-channel attention mechanisms and transfer learning approach on histopathology images by Muhammad Zubair, Muhammad Owais, Taimur Hassan, Malika Bendechache, Muzammil Hussain, Irfan Hussain, Naoufel Werghi

“…The proposed framework uses three different attention mechanism channels and convolutional neural networks to extract multichannel features during the classification process. …”
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TriageHD: A Hyper-Dimensional Learning-to-Rank Framework for Dynamic Micro-Segmentation in Zero-Trust Network Security by Ryozo Masukawa, Sanggeon Yun, Sungheon Jeong, Nathaniel D. Bastian, Mohsen Imani

“…This paper presents TriageHD, a novel framework that integrates graph-based Hyper-Dimensional Computing (HDC) with a learning-to-rank algorithm to strengthen zero-trust network security. …”
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Transfer learning based hybrid feature learning framework for enhanced skin cancer diagnosis using deep feature integration by Maridu Bhargavi, Sivadi Balakrishna

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Lightweight Dual-Stream SAR–ATR Framework Based on an Attention Mechanism-Guided Heterogeneous Graph Network by Xuying Xiong, Xinyu Zhang, Weidong Jiang, Tianpeng Liu, Yongxiang Liu, Li Liu

“…Additionally, we include a convolutional neural network based feature extraction net to replenish intuitive visual features. …”
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An Integrated Spatial-Spectral Denoising Framework for Robust Electrically Evoked Compound Action Potential Enhancement and Auditory Parameter Estimation by Fan-Jie Kung

“…Clean ECAP recordings help to accurately estimate auditory neural activity patterns and ECAP magnitudes, particularly through the panoramic ECAP (PECAP) framework. However, noise—especially in low-signal-to-noise ratio (SNR) conditions—can lead to significant errors in parameter estimation. …”
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A novel deep learning framework with artificial protozoa optimization-based adaptive environmental response for wind power prediction by Sangkeum Lee, Mohammad H. Almomani, Saleh Ali Alomari, Kashif Saleem, Aseel Smerat, Vaclav Snasel, Amir H. Gandomi, Laith Abualigah

“…To address these, this study proposes a novel hybrid deep learning framework, IAPO-LSTM, which combines Convolutional Neural Networks (CNNs) for spatial feature extraction and Gated Recurrent Units (GRUs) for temporal sequence modeling. …”
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ICT-Net: A Framework for Multi-Domain Cross-View Geo-Localization with Multi-Source Remote Sensing Fusion by Min Wu, Sirui Xu, Ziwei Wang, Jin Dong, Gong Cheng, Xinlong Yu, Yang Liu

“…To address these fundamental challenges of weak feature correlation and poor scene adaptation, we present a novel framework termed ICT-Net (Integrated CNN-Transformer Network) that synergistically combines convolutional neural networks with Transformer architectures. …”
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A machine learning-based recommendation framework for material extrusion fabricated triply periodic minimal surface lattice structures by Sajjad Hussain, Carman Ka Man Lee, Yung Po Tsang, Saad Waqar

“…To overcome these challenges, this study presents a machine learning (ML) and Deep Learning (DL) based framework recommending TPMS LS according to specific requirements. …”
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