Subdivision of river channel sand micro-scale facies with feature attention spatio-temporal network by Ruipu Zhao, Lili Zeng, Chendong Fu, Xiaoqing Zhao

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Advancing breast cancer diagnosis: Integrating deep transfer learning and U-Net segmentation for precise classification and delineation of ultrasound images by Divine Senanu Ametefe, Dah John, Abdulmalik Adozuka Aliu, George Dzorgbenya Ametefe, Aisha Hamid, Tumani Darboe

“…Three pre-trained convolutional neural networks (CNNs), including VGG16, VGG19, and EfficientNet were implemented within a deep transfer learning framework due to their strong feature extraction capabilities. …”
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A practical temporal transfer learning model for multi-step water quality index forecasting using A CNN-coupled dual-path LSTM network by Kok Poh Wai, Chai Hoon Koo, Yuk Feng Huang, Woon Chan Chong, Ahmed El-Shafie, Mohsen Sherif, Ali Najah Ahmed

“…Study focus: This study presents a multi-step ahead water quality index (WQI) forecasting framework in Klang River to address persistent challenges such as missing data and seasonally variable hydrological patterns. …”
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A fashion product recommendation based on adaptive VPKNN-NET algorithm without fuzzy similar image by R. Sabitha, D. Sundar

“…Traditional keyword-based systems often struggle to capture subjective style preferences.MethodsThis study proposes a novel fashion recommendation framework using an Adaptive VPKNN-net algorithm. The model integrates deep visual feature extraction using a pre-trained VGG16 Convolutional Neural Network (CNN), dimensionality reduction through Principal Component Analysis (PCA), and a modified K-Nearest Neighbors (KNN) algorithm that combines Euclidean and cosine similarity metrics to enhance visual similarity assessment.ResultsExperiments were conducted using the “Fashion Product Images (Small)” dataset from Kaggle. …”
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Leveraging Vision Foundation Model via PConv-Based Fine-Tuning with Automated Prompter for Defect Segmentation by Yifan Jiang, Jinshui Chen, Jiangang Lu

“…To address these issues, we propose PA-SAM, an industrial defect segmentation framework based on SAM. Firstly, to bridge the gap between SAM’s pre-training data and distinct characteristics of industrial defects, we introduce a parameter-efficient fine-tuning (PEFT) technique incorporating lightweight Multi-Scale Partial Convolution Aggregation (MSPCA) into Low-Rank Adaptation (LoRA), named MSPCA-LoRA, which effectively enhances the image encoder’s sensitivity to prior knowledge biases, while maintaining PEFT efficiency. …”
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Swin-GAT Fusion Dual-Stream Hybrid Network for High-Resolution Remote Sensing Road Extraction by Hongkai Zhang, Hongxuan Yuan, Minghao Shao, Junxin Wang, Suhong Liu

“…By decoupling detailed feature extraction from global context modeling, the proposed framework more faithfully represents complex road structures. …”
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Enhanced Offline Writer Recognition System Employing Blended Multi-Input CNN and Bi-LSTM Model on Diverse Handwritten Texts by Naresh Purohit, Subhash Panwar

“…This paper presents a complete framework that emphasizes feature engineering and uses a simple, efficient deep neural network. …”
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Key Frame Detection in Badminton Swings and Its Application to Physical Education by Jen-Hao Hsu, Chi-Chuan Lee, Jing-Yuan Chang, Duan-Shin Lee

“…Our proposed method uses the MediaPipe framework to extract 3D coordinates of skeleton joints, which serve as input features for a machine learning based model that accurately predicts key frame positions in badminton swing videos. …”
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Fourier Neural Operator Networks for Solving Reaction–Diffusion Equations by Yaobin Hao, Fangying Song

“…In this paper, we used Fourier Neural Operator (FNO) networks to solve reaction–diffusion equations. The FNO is a novel framework designed to solve partial differential equations by learning mappings between infinite-dimensional functional spaces. …”
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Integrating fast iterative filtering and ensemble neural network structure with attention mechanism for carbon price forecasting by Wang Zhong, Wang Yue, Wang Haoran, Tang Nan, Wang Shuyue

“…To address this challenge, this study proposes a novel integrated prediction framework designed to enhance forecast accuracy. First, the carbon price series is decomposed into a series of smoother subsequences using fast iterative filtering (FIF). …”
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YOLO-RD: A Road Damage Detection Method for Effective Pavement Maintenance by Wei Wang, Xiaoru Yu, Bin Jing, Ziqi Tang, Wei Zhang, Shengyu Wang, Yao Xiao, Shu Li, Liping Yang

“…To address these issues, we propose YOLO-RD, an advanced detection framework that integrates innovative modules for feature enhancement, multi-scale robustness, and detail preservation. …”
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An Ensemble Deep CNN Approach for Power Quality Disturbance Classification: A Technological Route Towards Smart Cities Using Image-Based Transfer by Mirza Ateeq Ahmed Baig, Naeem Iqbal Ratyal, Adil Amin, Umar Jamil, Sheroze Liaquat, Haris M. Khalid, Muhammad Fahad Zia

“…However, recent advancements have introduced Deep Convolution Neural Networks (DCNNs) as promising methods for the detection and classification of PQDs. …”
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Biologically inspired hybrid model for Alzheimer’s disease classification using structural MRI in the ADNI dataset by Houmem Slimi, Imen Cherif, Sabeur Abid, Mounir Sayadi

“…By bridging deep learning with neuromorphic principles, this work advances AD diagnostic frameworks, offering a computationally efficient and biologically plausible approach for clinical neuroimaging. …”
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Forecasting Tunnel-Induced Ground Settlement: A Hybrid Deep Learning Approach and Traditional Statistical Techniques With Sensor Data by Syed Mujtaba Hussaine, Linlong Mu, Yimin Lu, Syed Sajid Hussain

“…The proposed DL models, Convolutional Long Short-Term Memory (Conv-LSTM2D) and Convolutional Gated Recurrent Unit (Conv-GRU2D), extend traditional LSTM and GRU architectures with 2D convolutional mechanisms to capture complex spatiotemporal dependencies. …”
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Interpretable multitask deep learning model for detecting and analyzing severity of rice bacterial leaf blight by Sudhesh K. M, Aarthi R., Sainamole Kurian. P, Sikha O.K

“…This study introduces RCAMNet, a novel multi-task framework designed for accurate classification and severity analysis of BLB. …”
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Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network by Qingguo Wei, Chang Li, Yijun Wang, Xiaorong Gao

“…To address this issue, we propose a classification framework named eTRCA + sbCNN that combines an ensemble task-related component analysis (eTRCA) algorithm and a sub-band convolutional neural network (sbCNN) for recognizing the frequency of SSVEP signals. …”
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Classification of Hyperspectral Images of Explosive Fragments Based on Spatial–Spectral Combination by Donge Zhao, Peiyun Yu, Feng Guo, Xuefeng Yang, Yayun Ma, Changli Wang, Kang Li, Wenbo Chu, Bin Zhang

“…In order to extract effective features from redundant spectral information and improve classification accuracy, this paper adopted a classification framework based on deep learning. This framework used a convolutional neural network–bidirectional long short-term memory network (CNN-BiLSTM) as the spectral information classification model and a U-shaped network (U-Net) as the spatial segmentation model. …”
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Boosting Arabic text classification using hybrid deep learning approach by Eman Alnagi, Rawan Ghnemat, Qasem Abu Al-Haija

“…In this paper, we develop a hybrid deep learning framework for Arabic text classification, using the Inception-CNN (introduced in the GoogleNet architecture) and the LSTM (variation of the Recurrent Neural Network). …”
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Deep learning and wavelet packet transform for fault diagnosis in double circuit transmission lines by Ziad M. Ali, Ehab M. Esmail

“…This paper proposes an advanced directional protection framework that integrates wavelet packet transform (WPT) with deep learning (DL) models, utilizing double-ended measurements of three-phase currents and voltages. …”
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Cuff-less blood pressure monitoring via PPG signals using a hybrid CNN-BiLSTM deep learning model with attention mechanism by Hanieh Mohammadi, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

“…This paper introduces an advanced deep learning framework for precise, non-invasive BP estimation via photoplethysmography (PPG) signals, addressing critical limitations in traditional, cuff-based BP measurement methods. …”
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