MAMNet: Lightweight Multi-Attention Collaborative Network for Fine-Grained Cropland Extraction from Gaofen-2 Remote Sensing Imagery by Jiayong Wu, Xue Ding, Jinliang Wang, Jiya Pan

“…First, we reconstruct the ResNet-18 backbone network using deep separable convolutions, reducing computational complexity while preserving feature representation capabilities. …”
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SRW-YOLO: A Detection Model for Environmental Risk Factors During the Grid Construction Phase by Yu Zhao, Fei Liu, Qiang He, Fang Liu, Xiaohu Sun, Jiyong Zhang

“…To address these issues, we propose a one-stage SRW-YOLO algorithm built upon the YOLOv11 framework. First, a P2-scale shallow feature detection layer is added to capture high-resolution fine details of small targets. …”
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Early Breast Cancer Prediction Using Thermal Images and Hybrid Feature Extraction-Based System by Doaa Youssef, Hanan Atef, Shaimaa Gamal, Jala El-Azab, Tawfik Ismail

“…These findings show the significant advantages of the proposed framework for early prediction of breast cancer using thermal images.…”
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Implementation for Lightweight Deep Learning for Anomaly Detection and Denoising on Gravitational Waves by R. K. Mohith Niranjen, C. Yogesh, Anirudh Vinodh, Tharun Sureshkumar, S. Vatchala

“…Motivated by the WaveNet model, our method uses dilated convolutions to precisely model long-term dependencies in the data ensuring that subtle characteristics are captured. …”
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FP-Deeplab: A Novel Face Parsing Network for Fine-Grained Boundary Detection and Semantic Understanding by Borui Zeng, Can Shu, Ziqi Liao, Jingru Yu, Zhiyu Liu, Xiaoyan Chen

“…To address these challenges, this paper proposes a facial parsing network based on the Deeplabv3+ framework, named FP-Deeplab, which aims to improve segmentation performance and generalization capability through structurally enhanced modules. …”
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DGSS-YOLOv8s: A Real-Time Model for Small and Complex Object Detection in Autonomous Vehicles by Siqiang Cheng, Lingshan Chen, Kun Yang

“…To address these issues, this paper introduces DGSS-YOLOv8s, a model designed to enhance detection accuracy and high-FPS performance within the You Only Look Once version 8 small (YOLOv8s) framework. The key innovation lies in the synergistic integration of several architectural enhancements: the DCNv3_LKA_C2f module, leveraging Deformable Convolution v3 (DCNv3) and Large Kernel Attention (LKA) for better the capture of complex object shapes; an Optimized Feature Pyramid Network structure (Optimized-GFPN) for improved multi-scale feature fusion; the Detect_SA module, incorporating spatial Self-Attention (SA) at the detection head for broader context awareness; and an Inner-Shape Intersection over Union (IoU) loss function to improve bounding box regression accuracy. …”
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Efficient Identification and Classification of Pear Varieties Based on Leaf Appearance with YOLOv10 Model by Niman Li, Yongqing Wu, Zhengyu Jiang, Yulu Mou, Xiaohao Ji, Hongliang Huo, Xingguang Dong

“…YOLOv10 based on the PyTorch framework was applied to train the leaf dataset, and construct a pear leaf identification and classification model. …”
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Green Apple Detection Method Based on Multidimensional Feature Extraction Network Model and Transformer Module by Wei Ji, Kelong Zhai, Bo Xu, Jiawen Wu

“…To enhance the fast and accurate detection of pollution-free green apples for food safety, this paper uses the DETR network as a framework to propose a new method for pollution-free green apple detection based on a multidimensional feature extraction network and Transformer module. …”
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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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