Intelligent deep learning architecture for precision vegetable disease detection advancing agricultural new quality productive forces by Jun Liu, Xuewei Wang, Qian Chen, Peng Yan, Dugang Guo

“…To tackle these challenges, this study proposes YOLO-vegetable, a high-precision detection algorithm based on improved You Only Look Once version 10 (YOLOv10). The framework incorporates three innovative modules. The Adaptive Detail Enhancement Convolution (ADEConv) module employs dynamic parameter adjustment to preserve fine-grained features while maintaining computational efficiency. …”
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HiDRA-DCDNet: Dynamic Hierarchical Attention and Multi-Scale Context Fusion for Real-Time Remote Sensing Small-Target Detection by Jiale Wang, Zhe Bai, Ximing Zhang, Yuehong Qiu, Fan Bu, Yuancheng Shao

“…With 8.1 GFLOPs computational complexity and 2.6 ms inference speed per image, our framework demonstrates practical efficacy for real-time remote sensing applications, achieving superior accuracy–efficiency trade-off compared to existing approaches.…”
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YOLOv7scb: A Small-Target Object Detection Method for Fire Smoke Inspection by Dan Shao, Yu Liu, Guoxing Liu, Ning Wang, Pu Chen, Jiaxun Yu, Guangmin Liang

“…This approach incorporates two key improvements to the YOLOv7 framework: the use of space-to-depth convolution (SPD-Conv) and C3 modules, enhancing the model’s ability to extract features from small targets effectively. …”
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Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

“…To address these limitations, we propose the Fuzzy Graph Attention Network (FGATN), a novel intrusion detection framework that fuses fuzzy logic, graph attention mechanisms, and GNNs to deliver high accuracy and robustness in IIoT environments. …”
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BDSER-InceptionNet: A Novel Method for Near-Infrared Spectroscopy Model Transfer Based on Deep Learning and Balanced Distribution Adaptation by Jianghai Chen, Jie Ling, Nana Lei, Lingqiao Li

“…To address these limitations, this study proposes a novel transfer learning framework integrating multi-scale network architecture with Balanced Distribution Adaptation (BDA) to enhance cross-instrument compatibility. …”
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ECOLOGICAL RESILIENCE ASSESSMENT FEATURES OF NATURAL-INDUSTRIAL SYSTEMS BY INDEX-BASED METHODS USING SOFT COMPUTING by A.V. Masloboev

“…The unified methodological framework of our study includes the fundamentals of safety sciences, risk management methodology, and the stateof- the-art resilience concept of complex systems, as currently developing research area. …”

Multi-Scale Feature Mixed Attention Network for Cloud and Snow Segmentation in Remote Sensing Images by Liling Zhao, Junyu Chen, Zichen Liao, Feng Shi

“…This work proposes a Multi-scale Feature Mixed Attention Network (MFMANet). The framework integrates three key components: (1) a Multi-scale Pooling Feature Perception Module to capture multi-level structural features, (2) a Bilateral Feature Mixed Attention Module that enhances boundary detection through spatial-channel attention, and (3) a Multi-scale Feature Convolution Fusion Module to reduce edge blurring. …”
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Predicting the Imbalanced Impact of Drugs on Microbial Abundance Using Multi-View Learning and Data Augmentation by Bei Zhu, Haoyang Yu, Bingxue Du, Hui Yu, Jianyu Shi

“…To address these issues, we propose a framework for predicting the imbalanced Impact of Drugs on Microbial Abundance by leveraging Multi-view Learning and Data Augmentation, named IDMA-MLDA. …”
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YOLOv8n-DSDL: A lightweight dual-backbone network with decoupled self-attention for cotton maturity detection by Meiqi Zhong, Linjing Wei, Henghui Mo

“…A novel Decoupled Focused Self-Attention (DFSA) mechanism is designed, which utilizes one-dimensional dilated convolutions and key-value fusion operations to dynamically enhance feature associations and improve perception of subtle visual cues such as color variation and micro-cracks. …”
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High-Precision Pose Measurement of Containers on the Transfer Platform of the Dual-Trolley Quayside Container Crane Based on Machine Vision by Jiaqi Wang, Mengjie He, Yujie Zhang, Zhiwei Zhang, Octavian Postolache, Chao Mi

“…A multi-scale adaptive frequency object-detection framework is developed based on YOLO11, achieving improved detection accuracy for multi-scale lockhole keypoints in perspective-distortion scenarios (mAP@0.5 reaches 95.1%, 4.7% higher than baseline models) through dynamic balancing of high–low-frequency features and adaptive convolution kernel adjustments. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…On the other hand, to reduce feature dilution and computational redundancy in traditional detection heads when focusing on small targets, we replace conventional convolutions with simple linear transformations and design a lightweight detection head, LSD-Head. …”
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High‐order multilayer attention fusion network for 3D object detection by Baowen Zhang, Yongyong Zhao, Chengzhi Su, Guohua Cao

“…To enhance the expressive power between different modality features, we introduce a high‐order feature fusion module that performs multi‐level convolution operations on the element‐wise summed features. …”
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EOD-EMDA: A method for automatically identifying and tracking individual pigs in herds by Wei Li, Hu Yuan, Xianpeng Zhu, Xiaojiang Yang

“…In tracking tasks, EOD+EMDA outperforms five popular algorithms (SORT, DeepSORT, ByteTrack, StrongSORT, and OC-SORT), achieving superior results in IDs, IDF1, IDP, IDR, and MOTA.Field tests demonstrate that the proposed framework enables accurate, stable, and real-time tracking of pigs from oblique perspectives. …”
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IoT-Enhanced Smart Parking Management With IncepDenseMobileNet for Improved Classification by Xiaoxia Zheng, Wenxi Feng, Ning Wang, Huhemandula

“…This paper presents an innovative framework for improving parking operations, dynamic pricing, and resource allocation in urban environments.…”
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Photon–photon chemical thermodynamics of frequency conversion processes in highly multimode systems by Huizhong Ren, Georgios G. Pyrialakos, Qi Zhong, Fan O. Wu, Mercedeh Khajavikhan, Demetrios N. Christodoulides

“…By utilizing fundamental notions from optical statistical mechanics, we develop a universal theoretical framework that effectively treats all frequency components as chemical reactants/products, capable of undergoing optical thermodynamic reactions facilitated by a variety of multi-wave mixing effects. …”
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Physics-Guided Self-Supervised Learning Full Waveform Inversion with Pretraining on Simultaneous Source by Qiqi Zheng, Meng Li, Bangyu Wu

“…The inversion network is a partial convolution attention modified UNet (PCAMUNet), which combines local feature extraction with global information integration to achieve high-resolution velocity model estimation from seismic shot gathers. …”
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ST-MSRN: An enhanced spatio-temporal super-resolution model for complex meteorological data reconstruction by Ping Mei, Zhi Yang, Changzheng Liu, Lei Wang, Zixin Yin

“…To address these limitations, this study proposes a Spatio-Temporal Multi-Scale Residual Network (ST-MSRN), which integrates a Multi-Scale Residual Feature Block (MSRFB) with a Channel Stacking Mechanism. The framework employs parallel multi-scale convolutions to hierarchically extract meteorological patterns, while the integrated Efficient Multi-scale Attention (EMA) module adaptively weights features based on spatio-temporal heterogeneity. …”
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Kinematic Integration Network With Enhanced Temporal Intelligence and Quality-Driven Attention for Precise Joint Angle Prediction in Exoskeleton-Based Gait Analysis by Lyes Saad Saoud, Irfan Hussain

“…This study introduces KINETIQA (Kinematic Integration Network with Enhanced Temporal Intelligence and Quality-Driven Attention), a novel predictive framework that advances the state of the art in knee angle prediction, demonstrating significant improvements in accuracy and clinical utility. …”
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A novel image fusion method based on UAV and Sentinel-2 for environmental monitoring by Fan Zhang, Aobo Guo, Zhenqi Hu, Yusheng Liang

“…Results demonstrate that the stacked learning model, combined with cubic convolution resampling, reduces the MAPE of NDVI values between Sentinel-2 and UAV imagery from 54.31 to 10.01%, markedly improving accuracy. …”
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DCCPNet: A Dual-Branch Channel Cross-Concatenation Pan-Sharpening Network for Satellite Remote Sensing Imagery by Zechun Li, Xunqiang Gong, Ailong Ma, Haiqing He, Pengyuan Lv, Xiansan Liu, Yanfei Zhong

“…., DCCPNet, is proposed, which introduces DCC blocks to facilitate bidirectional feature exchange between panchromatic and multispectral branches. Within this framework, hierarchical features are extracted through multiscale convolution residual (MCR) blocks, while complementary spatial and spectral information is adaptively fused in the DCC blocks. …”
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