YOLO-SRMX: A Lightweight Model for Real-Time Object Detection on Unmanned Aerial Vehicles by Shimin Weng, Han Wang, Jiashu Wang, Changming Xu, Ende Zhang

“…To tackle these difficulties, this study introduces YOLO-SRMX, a lightweight real-time object detection framework specifically designed for infrared imagery captured by UAVs. …”
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Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening by Yanjie Sun, Xiaolong Song, Zhi Li, Haijue Xu, Yuchuan Bai

“…The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. …”
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Robust scale fusion and edge-aware feature attention network for remote sensing UAV road detection under harsh weather by Jialang Liu, Jialei Zhan, Jiehua Zhang, Jiangming Chen, Yan Song, Lixing Tang, Le Zhou, Chengsi Du, Yingmei Wei, Yanming Guo

“…To address these issues, we propose RSFC-EAFANet, a robust detection framework that integrates Robust Scale Fusion Convolution (RSFC) with an Edge-aware Adaptive Feature Aggregation (EAFA) module. …”
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An improved ShuffleNetV2 method based on ensemble self-distillation for tomato leaf diseases recognition by Shuiping Ni, Yue Jia, Mingfu Zhu, Mingfu Zhu, Yizhe Zhang, Wendi Wang, Shangxin Liu, Yawei Chen

“…To address this issue, this study proposes an ensemble self-distillation method and applies it to the lightweight model ShuffleNetV2.MethodsSpecifically, based on the architecture of ShuffleNetV2, multiple shallow models at different depths are constructed to establish a distillation framework. Based on the fused feature map that integrates the intermediate feature maps of ShuffleNetV2 and shallow models, a depthwise separable convolution layer is introduced to further extract more effective feature information. …”
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A Lightweight Model for Weed Detection Based on the Improved YOLOv8s Network in Maize Fields by Jinyong Huang, Xu Xia, Zhihua Diao, Xingyi Li, Suna Zhao, Jingcheng Zhang, Baohua Zhang, Guoqiang Li

“…Finally, Dualconv was employed instead of the conventional convolution for downsampling, further diminishing the network load. …”
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Handwritten Urdu Characters and Digits Recognition Using Transfer Learning and Augmentation With AlexNet by Aqsa Rasheed, Nouman Ali, Bushra Zafar, Amsa Shabbir, Muhammad Sajid, Muhammad Tariq Mahmood

“…The purpose of this research is to present a classification framework for automatic recognition of handwritten Urdu character and digits with higher recognition accuracy by utilizing theory of transfer learning and pre-trained Convolution Neural Networks (CNN). …”
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A lightweight mechanism for vision-transformer-based object detection by Yanming Ye, Qiang Sun, Kailong Cheng, Xingfa Shen, Dongjing Wang

“…However, the attention mechanism-based detection framework of DETR exhibits limitations in small and medium-sized object detection. …”
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Leveraging Frozen Foundation Models and Multimodal Fusion for BEV Segmentation and Occupancy Prediction by Seamie Hayes, Ganesh Sistu, Ciaran Eising

“…In Bird's Eye View perception, significant emphasis is placed on deploying well-performing, convoluted model architectures and leveraging as many sensor modalities as possible to reach maximal performance. …”
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DAU-YOLO: A Lightweight and Effective Method for Small Object Detection in UAV Images by Zeyu Wan, Yizhou Lan, Zhuodong Xu, Ke Shang, Feizhou Zhang

“…In this paper, we propose DAU-YOLO, a novel object detection method tailored for drone imagery, built upon the YOLOv11 framework. To enhance feature extraction, a Receptive-Field Attention (RFA) module is introduced in the backbone, allowing adaptive convolution kernel adjustments across different local regions, thereby addressing the challenge of dense object distributions. …”
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A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models by Hamidreza Najafi, Kimia Savoji, Marzieh Mirzaeibonehkhater, Seyed Vahid Moravvej, Roohallah Alizadehsani, Siamak Pedrammehr

“…This GAN, equipped with dilated convolution layers in its discriminator, captures extensive contextual information, enabling the accurate reconstruction of the tumor’s 3D structure. …”
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Enhancing Object Detection in Underground Mines: UCM-Net and Self-Supervised Pre-Training by Faguo Zhou, Junchao Zou, Rong Xue, Miao Yu, Xin Wang, Wenhui Xue, Shuyu Yao

“…The self-supervised pre-training framework effectively enhances training efficiency, enabling UCM-Net to attain an average mAP₅₀ of 94.4% across all five datasets. …”
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Polarization-sensitive in-sensor computing in chiral organic integrated 2D p-n heterostructures for mixed-multimodal image processing by Je-Jun Lee, Seong-Jun Han, Changsoon Choi, Chaewon Seo, Seungkwon Hwang, Jihyun Kim, Jung Pyo Hong, Jisu Jang, Jihoon Kyhm, Jung Woo Kim, Byoung-Soo Yu, Jung Ah Lim, Gunuk Wang, Joohoon Kang, Yonghun Kim, Suk-kyun Ahn, Jongtae Ahn, Do Kyung Hwang

“…By effectively integrating polarization-sensitive detectors into the in-sensor computing framework, the proposed architecture preserves kernel optimization capabilities while simplifying circuit complexity.…”
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Enhanced Swine Behavior Detection with YOLOs and a Mixed Efficient Layer Aggregation Network in Real Time by Ji-hyeon Lee, Yo Han Choi, Han-sung Lee, Hyun Ju Park, Jun Seon Hong, Ji Hwan Lee, Soo Jin Sa, Yong Min Kim, Jo Eun Kim, Yong Dae Jeong, Hyun-chong Cho

“…This study developed a system, termed mixed-ELAN, for real-time sow and piglet behavior detection using an extended ELAN architecture with diverse kernel sizes. The standard convolution operations within the ELAN framework were replaced with MixConv using diverse kernel sizes to enhance feature learning capabilities. …”
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RSEFormer: A Residual Squeeze-Excitation-Based Transformer for Pixelwise Hyperspectral Image Classification by Yusen Liu, Hao Zhang, Fashuai Li, Fei Han, Yicheng Wang, Hao Pan, Boyu Liu, Guoliang Tang, Genghua Huang, Tingting He, Yuwei Chen

“…To this end, we propose a network that combines local spectral attention and global spatial-spectral attention, the residual depthwise separable squeeze-and-extraction transformer for HSI classification. Our framework integrates 3-D depthwise separable convolution (DSC) squeeze-and–excitation module, residual block, and sharpened attention vision transformer (SA-ViT) to extract spatial-spectral features from HSI. …”
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Extraction of <i>Suaeda salsa</i> from UAV Imagery Assisted by Adaptive Capture of Contextual Information by Ning Gao, Xinyuan Du, Min Yang, Xingtao Zhao, Erding Gao, Yixin Yang

“…Evaluation metrics including the accuracy, recall, F1 score, and mIou all exceed 90%. (3) Comparative experiments with state-of-the-art semantic segmentation models reveal that our framework significantly improves the extraction accuracy, particularly for low-contrast and diminutive <i>Suaeda salsa</i> targets. …”
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VeloFHE: GPU Acceleration for FHEW and TFHE Bootstrapping by Shiyu Shen, Hao Yang, Zhe Liu, Ying Liu, Xianhui Lu, Wangchen Dai, Lu Zhou, Yunlei Zhao, Ray C. C. Cheung

“…Additionally, we explore batching in bootstrapping, de- veloping a general framework that accommodates both schemes with either gadget decomposition or modulus raising method. …”
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STYLISTIC MEANS OF IMPLEMENTING THE IDEA OF THE WORLD’S IRIDESCENCE IN PH.K. DICK’S “UBIK” IN THE CONTEXT OF TRANSLATION TRANSFORMATIONS by Svitlana F. Aleksenko, Larysa I. Taranenko

“…The article deals with the formation means of the idea of the world’s iridescence or illusiveness, its stylistic and translation aspects within the textual framework of Ph.K. Dick’s novel “Ubik” and its translat- ed version in Ukrainian. …”
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Attention-Based Hypergraph Neural Network: A Personalized Recommendation by Peihua Xu, Maoyuan Zhang

“…The method establishes computational frameworks for hyperedge-vertex coefficient matrices and inter-hyperedge attention scores, effectively capturing high-order nonlinear correlations within multimodal heterogeneous data, while employing temporal attention units to track the evolution of user preferences. …”
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Comparative evaluation of deep learning and machine learning techniques for sentiment analysis of electronic product review data by Nagelli Archana, Saleena B., Prakash B.

“…To evaluate the performance of various machine learning and deep learning techniques, frameworks, F1 score, precision, recall as well as, accuracy was used. …”
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A Novel Network for Choroidal Segmentation Based on Enhanced Boundary Information by Wenbo Huang, Chaofan Qu, Yang Yan

“…Moreover, the modular design of the boundary enhancement module ensures its portability across different segmentation tasks, making it a versatile component for integration into existing frameworks.…”
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