WRRT-DETR: Weather-Robust RT-DETR for Drone-View Object Detection in Adverse Weather by Bei Liu, Jiangliang Jin, Yihong Zhang, Chen Sun

“…To address the challenges of scale variation and visual degradation introduced by harsh weather, we propose WRRT-DETR, a weather-robust object detection framework optimized for small objects. Within this framework, we design a gated single-head global–local attention backbone block (GLCE) to fuse local convolutional features with global attention, enhancing small object distinguishability. …”
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Constraint-aware wind power forecasting with an optimized hybrid machine learning model by Md. Omer Faruque, Md. Alamgir Hossain, S.M. Mahfuz Alam, Muhammad Khalid

“…In response, this paper introduces a novel constraint aware forecasting framework formed by a convolutional neural network (CNN) integrated with a double layer of gated recurrent unit (GRU) and fully connected layers. …”
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Integrating UAV-Based Multispectral Data and Transfer Learning for Soil Moisture Prediction in the Black Soil Region of Northeast China by Tong Zhou, Shoutian Ma, Tianyu Liu, Shuihong Yao, Shenglin Li, Yang Gao

“…This framework involves pre-training a model on a source domain and fine-tuning it with a limited set of target domain samples to achieve high-precision SM inversion. …”
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Utilizing deep learning for intelligent monitoring and early warning of slope disasters in public space design by Wang Ting, Ying Wang

“…The integration of neural network-based prediction with adaptive spatial planning enhances both the precision and timeliness of disaster warnings.DiscussionThis framework offers a transformative, safe, and functional approach to slope disaster management in dynamic public spaces. …”
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Graph Neural Network With Hessian-Based Locally Linear Embedding for Cancer Metastasis Analysis in Lymph Nodes Using DeepLab Segmentation by Senthil Jayapal, R. Annamalai

“…The proposed framework integrates DeepLab, a highly advanced convolutional neural network for image segmentation, to segment the lymph node regions from high-resolution MRI and PET scans. …”
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Resolution-Aware Deep Learning with Feature Space Optimization for Reliable Identity Verification in Electronic Know Your Customer Processes by Mahasak Ketcham, Pongsarun Boonyopakorn, Thittaporn Ganokratanaa

“…To address these challenges, this study proposes a novel and robust identity verification framework that integrates super-resolution preprocessing, a convolutional neural network (CNN), and Monte Carlo dropout-based Bayesian uncertainty estimation for enhanced facial recognition in electronic know your customer (e-KYC) processes. …”
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MedAlmighty: enhancing disease diagnosis with large vision model distillation by Yajing Ren, Zheng Gu, Wen Liu

“…In this approach, we utilize DINOv2—a pre-trained large vision model—as a frozen teacher, and a lightweight convolutional neural network (CNN) as the trainable student. …”
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Urban Functional Zone Mapping by Integrating Multi-Source Data and Spatial Relationship Characteristics by Daoyou Zhu, Xu Dang, Wenjia Shi, Yixiang Chen, Wenmei Li

“…This framework leverages the OpenStreetMap (OSM) road network to partition the study area into functional units, employs a graph model to represent urban functional nodes and their intricate spatial topological relationships, and harnesses the capabilities of Graph Convolutional Network (GCN) to fuse these multi-dimensional features through end-to-end learning for accurate urban function discrimination. …”
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Temporal Dynamics in Short Text Classification: Enhancing Semantic Understanding Through Time-Aware Model by Khaled Abdalgader, Atheer A. Matroud, Ghaleb Al-Doboni

“…These results underscore the potential of the proposed framework to provide deeper insights into the evolving nature of language and its impact on short-text classification. …”
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Educational Psychology Analysis Method for Extracting Students’ Facial Information Based on Image Big Data by Maoyue Zhang

“…The image data type and input and output format based on MapReduce framework are designed, and the image data is optimized by means of serialized files. …”
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Intelligent data-driven system for mold manufacturing using reinforcement learning and knowledge graph personalized optimization for customized production by Chengcai He, Jiaxing Deng, Jingchun Wu, Beicheng Qin, Jinxiang Chen, Yan Li, Qiangsheng Huang

“…The experimental results reveal two key findings: (1) Within the enhanced learning knowledge graph framework, the algorithm—optimized using a graph convolutional network—achieves consistently higher qualification rates across test samples. …”
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MSDCA: A Multi-Scale Dual-Branch Network with Enhanced Cross-Attention for Hyperspectral Image Classification by Ning Jiang, Shengling Geng, Yuhui Zheng, Le Sun

“…To address these limitations, we propose a dual-branch deep learning framework named MSDCA, which performs spatial–spectral joint modeling under limited supervision. …”
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Fast Reverse Design of 4D‐Printed Voxelized Composite Structures Using Deep Learning and Evolutionary Algorithm by Mengtao Wang, Zaiyang Liu, Hidemitsu Furukawa, Zhuo Li, Yifei Ge, Yifan Xu, Zhe Qiu, Yang Tian, Zhongkui Wang, Ren Xu, Lin Meng

“…Furthermore, a progressive evolutionary algorithm (PEA) is proposed by integrating the DL model to construct a DL‐PEA framework. This framework supports rapid reverse engineering of the desired shape, and the average design time for specified target shapes is reduced to ≈3.04 s. …”
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A multi-patch-based deep learning model with VGG19 for breast cancer classifications in the pathology images by Anitha Ponraj, Palanigurupackiam Nagaraj, Duraisamy Balakrishnan, Parvathaneni Naga Srinivasu, Jana Shafi, Wonjoon Kim, Muhammad Fazal Ijaz

“…This study introduces a novel method, MPa-DCAE, which uses a multi-patch-based deep convolutional auto-encoder (DCAE) framework combined with VGG19 to detect and classify breast cancer in histopathology images. …”
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IoTShield: Defending IoT Systems Against Prevalent Attacks Using Programmable Networks by Mah-Rukh Fida, Azza H. Ahmed, Ameer Shakayb Arsalaan

“…This paper presents <monospace>IoTShield</monospace>, a Software Defined Network (SDN) based dual-stage defensive framework, designed to mitigate different flow-based attacks targeting IoT systems. …”
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GazeMap: Dual-Pathway CNN Approach for Diagnosing Alzheimer’s Disease from Gaze and Head Movements by Hyuntaek Jung, Shinwoo Ham, Hyunyoung Kil, Jung Eun Shin, Eun Yi Kim

“…This study proposes a novel AD detection framework integrating gaze and head movement analysis via a dual-pathway convolutional neural network (CNN). …”
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VMKLA-UNet: vision Mamba with KAN linear attention U-Net by Chenhong Su, Xuegang Luo, Shiqing Li, Li Chen, Juan Wang

“…Abstract In the domain of medical image segmentation, while convolutional neural networks (CNNs) and Transformer-based architectures have attained notable success, they continue to face substantial challenges. …”
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Federated learning applications in soil spectroscopy by Giannis Gallios, Nikolaos Tsakiridis, Nikolaos Tziolas

“…The results show that the FL framework can match, and in some cases exceed, the performance of centralized models, particularly when using IID data. …”
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Efficient Generative-Adversarial U-Net for Multi-Organ Medical Image Segmentation by Haoran Wang, Gengshen Wu, Yi Liu

“…This paper introduces a novel medical image-segmentation framework named Efficient Generative-Adversarial U-Net (EGAUNet), designed to facilitate rapid and accurate multi-organ labeling. …”
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Toward Adaptive Unsupervised and Blind Image Forgery Localization with ViT-VAE and a Gaussian Mixture Model by Haichang Yin, KinTak U, Jing Wang, Wuyue Ma

“…Recently, several unsupervised approaches based on the variational autoencoder (VAE) framework have been proposed for forged pixel detection. …”
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