Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification by Pragati Patharia, Prabira Kumar Sethy, K. Lakshmipathi Raju, Anita Khanna, Ashoka Kumar Ratha, Santi Kumari Behera, Aziz Nanthaamornphong

“…This study proposes an advanced deep learning-based framework for classifying CRC histological images into eight categories: Adipose, Complex, Debris, Empty, Lympho, Mucosa, Stroma, and Tumor. …”
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Using Deep Learning in Forecasting the Production of Electricity from Photovoltaic and Wind Farms by Michał Pikus, Jarosław Wąs, Agata Kozina

“…This publication is based on the results obtained within the framework of the research and development project “POIR.01.01.01-00-0506/21”, realized in the years 2022–2023. …”
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Data-driven discovery of the design rules for considering the curing deformation and the application on double-double composites by Yizhuo Gui, Hongwei Song, Jinglei Yang, Cheng Qiu

“…In this regard, a data-driven framework was proposed in this paper to determine the layup rules to follow for minimizing PID. …”
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Smart system for real time monitoring and diagnosis of dengue surfaces in Bangladesh by Md. Shahriar Hossain Apu, Samsuddin Ahmed, Md. Toukir Ahmed

“…The integration of the Convolutional Block Attention Module (CBAM) enhances the model’s feature extraction capabilities, improving its focus on critical regions in the images. …”
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AI-based real-time prediction of cross-sectional phase distribution during laser heat treatment via sequential thermal imaging and image-to-image synthesis by Myeonggyun Son, Hyungson Ki

“…This study proposes the first AI-driven framework for real-time phase mapping during laser heat treatment of S45C steel, using sequential infrared surface temperature images. …”
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Optimization of Coverage Path Planning for Agricultural Drones in Weed-Infested Fields Using Semantic Segmentation by Fabian Andres Lara-Molina

“…In this direction, a novel framework for autonomous drone-based herbicide applications that integrates deep learning-based semantic segmentation and coverage path optimization is proposed. …”
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MLFF-SFNet: A Visual Perception-Guided Network for High-Accuracy Road Extraction in Remote Sensing Imagery via Multilevel Feature Fusion and Similarity Filtering by Kaiming Quan, Dongmei Yan, Ruyi Feng

“…The BDAM captures long-range dependencies of irregular roads through deformable convolutional kernels and bidirectional attention, while the DSN establishes skip connections with dilated convolutions to preserve edge details during multiscale FF. …”
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Automated diagnosis of mild cognitive impairment through connectivity analysis of EEG signals and a DL scheme by Jiayi Lin, Wei Huang

“…To investigate the hypothesis, a new signal processing technique was utilized to transform intricate EEGs into input images for a DL framework. For this purpose, an ensemble pre-trained convolutional neural network (CNN) is suggested to classify EEG signals of 66 AD patients, 61 MCI patients, and 60 healthy aging individuals. …”
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A NOVEL DEEP LEARNING APPROACHES FOR MULTI-CLASS HISTOPATHOLOGICAL SUB-IMAGE CLASSIFICATION USING PRIOR KNOWLEDGE by Riyam Ali Yassin, Morteza Valizadeh, Alaa Hussein Abdulaal

“…This study introduces a novel framework that combines transfer learning (TL) with an Incorporation of Prior Knowledge algorithm for multi-class classification of breast cancer using histopathological images. …”
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Spatio-Temporal Graph Neural Networks for Streamflow Prediction in the Upper Colorado Basin by Akhila Akkala, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Pouya Hosseinzadeh, Ayman Nassar

“…These results underscore the importance of integrating spatial dependencies and temporal dynamics in hydrological forecasting, offering a scalable and adaptable framework to improve predictive accuracy and support adaptive water resource management in river basins.…”
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Research on fusion generation algorithm of visual communication and product design based on AIGC technology by Guoying Chen, Xiaofeng Lan, Kai Liu, Can Cheng

“…This paper makes an in-depth analysis of the requirements of fusion of visual communication and product design, and puts forward the basic framework of fusion generation algorithm and the method of dynamic fusion of visual communication and product design elements based on convolutional neural network. …”
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A Systematic Review and Evaluation of Sustainable AI Algorithms and Techniques in Healthcare by Yehia Ibrahim Alzoubi, Ahmet E. Topcu, Ersin Elbasi

“…We propose an integration framework for deploying these methods in resource-constrained healthcare environments, identifying open research challenges and future directions. …”
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Efficient and low complex architecture for detection and classification of Brain Tumor using RCNN with Two Channel CNN by Nivea Kesav, M.G. Jibukumar

“…Brain tumor classification and detection is a subject of prime importance where Convolutional Neural Networks (CNN) find application. …”
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HE-BiDet: A Hardware Efficient Binary Neural Network Accelerator for Object Detection in SAR Images by Dezheng Zhang, Zehan Liang, Rui Cen, Zhihong Yan, Rui Wan, Dong Wang

“…To address this, we propose HE-BiDet, an ultra-lightweight Binary Neural Network (BNN) framework co-designed with hardware acceleration. First, we develop an ultra-lightweight SAR ship detection model. …”
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An Enhanced Bio-inspired GWO–DE Technique for Efficient Feature Selection in the EEG-RSVP Paradigm by S. Abinayaa, S. S. Sridhar

“…To resolve these issues, we present a bio-inspired hybrid optimization framework where Differential Evolution (DE) is integrated with Grey Wolf Optimization (GWO) to improve the efficiency of feature selections. …”
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Feature-informed machine learning for detecting material deformation and failure in aluminum pipes under bending load using acoustic emission sensors by Xiaowei Zuo, Nicholas Satterlee, Chang-Whan Lee, In-Gyu Choi, Choon-Wook Park, John S. Kang

“…Additionally, we propose a novel Feature-Informed Convolutional Neural Network (FI-CNN), which integrates the features into the CNN framework, yielding an accuracy of 92.7 %, outperforming the traditional machine learning methods. …”
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An integrated predictive model for Alzheimer’s disease progression from cognitively normal subjects using generated MRI and interpretable AI by Atefe Aghaei, Mohsen Ebrahimi Moghaddam

“…In this study, we propose an integrated framework that leverages ensemble transfer learning, generative modeling, and automatic ROI extraction techniques to predict the progression of Alzheimer’s disease from cognitively normal (CN) subjects. …”
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Deep learning-based surface deformation tracking with interferometric fringes: A case study in Taiwan by Shih-Teng Chang, Shih-Yuan Lin, Yu-Ching Lin

“…By enabling deformation detection across different magnitudes, time periods, and regions, the proposed framework offers a scalable and transferable solution for extending MT-InSAR-based surface hazard tracking.…”
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Multi-source data fusion-based knowledge transfer for unmanned aerial vehicle flight data anomaly detection and recovery by Lei Yang, Shaobo Li, Liya Yu, Caichao Zhu, Congbao Wang

“…First, a data-driven framework based on one-dimensional convolutional neural network and bi-directional long short-term memory (1D CNN-BiLSTM) with parameter selection and residual smoothing (1DCB-PSRS) is proposed. …”
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Benchmarking Deep Learning for Wetland Mapping in Denmark Using Remote Sensing Data by Muhammad Rizwan Asif

“…While remote sensing combined with deep learning (DL) offers a promising solution, inconsistencies in wetland classification systems—where different regions define wetland types based on their policy frameworks and conservation priorities—limit the applicability of these models. …”
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