SSMM-DS: A semantic segmentation model for mangroves based on Deeplabv3+ with swin transformer by Zhenhua Wang, Jinlong Yang, Chuansheng Dong, Xi Zhang, Congqin Yi, Jiuhu Sun

“…Using Deeplabv3+ as the basic framework, we first constructed a data concatenation module to improve the contrast between mangroves and other vegetation or water. …”
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Change Detection Network Based on Transformer and Transfer Learning by Hua Li, Jingyu Li, Guanghao Luo, Liang Zhou, Hao Wu, Zhangcai Yin

“…Currently, deep learning based change detection algorithms have achieved excellent detection results through the meticulous design of feature extraction and change judgment modules. However, challenges, such as limited generalization ability owing to small-scale change-detection datasets and noise generated by the change judgment module, still exist. …”
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MVS-GS: High-Quality 3D Gaussian Splatting Mapping via Online Multi-View Stereo by Byeonggwon Lee, Junkyu Park, Khang Truong Giang, Sungho Jo, Soohwan Song

“…Previous research has tackled this issue by incorporating Neural Radiance Fields (NeRF) or 3D Gaussian Splatting (3DGS) as scene representations within dense SLAM methods. …”
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An Improved YOLOv8 Model for Detecting Four Stages of Tomato Ripening and Its Application Deployment in a Greenhouse Environment by Haoran Sun, Qi Zheng, Weixiang Yao, Junyong Wang, Changliang Liu, Huiduo Yu, Chunling Chen

“…Through image processing techniques, the issue of class imbalance was addressed. Based on this, a model named GCSS-YOLO was proposed. …”
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A text clarification and deep relational reasoning method for Mongolian-Chinese bilingual arbitrary-shaped scene text detection by Yuefeng Liu, Liuxu Ding, Yunong Liu

“…In response to the substantial differences in script structure between Mongolian and Chinese, we apply a boundary point offset strategy to refine candidate bounding boxes, ensuring complete text instance coverage for both languages. To address the issue of blurred text images, we introduce a ClearText module for image restoration, which enhances the visibility of fine textual details and facilitates more accurate detection. …”
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MOMFNet: A Deep Learning Approach for InSAR Phase Filtering Based on Multi-Objective Multi-Kernel Feature Extraction by Xuedong Zhang, Cheng Peng, Ziqi Li, Yaqi Zhang, Yongxuan Liu, Yong Wang

“…MOMFNet incorporates a multi-objective loss function that accounts for both the spatial and statistical characteristics of the denoising results, while its multi-kernel convolutional feature extraction module captures multi-scale information comprehensively. …”
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Association of food insecurity with anemia in children and adolescents: a systematic review and meta-analysis of observational studies by Seyedeh Parisa Moosavian, Maryam Ghodsi, Parisa Farzanehnejad, Niloufar Ghanbari, Seyed Hossein Mirlohi, Sajjad Moradi

“…Abstract Background Food insecurity, characterized by limited access to adequate and safe foods, is a prevalent global issue affecting millions. Anemia, often stemming from insufficient iron intake, is a common health concern, especially in children. …”
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Potato precision planter metering system based on improved YOLOv5n-ByteTrack by Cisen Xiao, Changlin Song, Junmin Li, Min Liao, Yongfan Pu, Kun Du

“…Initially, the C3-Faster module is introduced, which reduces the number of parameters and computational load while maintaining detection accuracy. …”
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YOLO-UP: A High-Throughput Pest Detection Model for Dense Cotton Crops Utilizing UAV-Captured Visible Light Imagery by Chenglei Sun, Afizan Bin Azman, Zaiyun Wang, Xiaoxiao Gao, Kai Ding

“…YOLO-PEST incorporates a custom-designed SC3 module to enhance low-level feature extraction and employs the GeLU activation function to address the vanishing gradient issue. …”
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FFTL-Net: a network for the classification of skin diseases based on feature fusion and transfer learning by Xiaowei Song, Yurong Mei, Zhilei Zhao, Hao Chang, Lina Han, Hui Wang, Xinyi Zhang, Guoqiang Wang

“…The objective is to address the issues of data imbalance, overfitting, and inadequate generalization ability in skin disease datasets and recognition models. …”
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Graph-Based Adaptive Network With Spatial-Spectral Features for Hyperspectral Unmixing by Hua Dong, Xiaohua Zhang, Jinhua Zhang, Hongyun Meng, Licheng Jiao

“…In addition, an Adaptive Abundance Constraint Module is proposed to dynamically enforce constraints on the extracted features. …”
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Research on Bearing Fault Diagnosis Method for Varying Operating Conditions Based on Spatiotemporal Feature Fusion by Jin Wang, Yan Wang, Junhui Yu, Qingping Li, Hailin Wang, Xinzhi Zhou

“…Then, a parallel processing mechanism of the Convolutional Neural Network (SECNN) based on the Squeeze-and-Excitation module and the Bidirectional Long Short-Term Memory network (BiLSTM) is employed to dynamically adjust weights, capturing high-dimensional spatiotemporal features. …”
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Detection of Photovoltaic Arrays in High-Spatial-Resolution Remote Sensing Images Using a Weight-Adaptive YOLO Model by Zhumao Lu, Xiaokai Meng, Jinsong Li, Hua Yu, Shuai Wang, Zeng Qu, Jiayun Wang

“…This study addresses the issue of inadequate remote sensing monitoring accuracy for photovoltaic (PV) arrays in complex geographical environments against the backdrop of rapid global expansion in PV power generation. …”
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RUL Prediction for Lithium Battery Systems in Fuel Cell Ships Based on Adaptive Modal Enhancement Networks by Yifan Liu, Huabiao Jin, Xiangguo Yang, Telu Tang, Jiaxin Luo, Lei Han, Junting Lang, Weixin Zhao

“…The Squeeze-and-Excitation Networks (SEAttention) module is employed to enhance the accuracy of feature extraction, and the sparse attention mechanism of Informer is utilized to efficiently model long-term dependencies in time series. …”
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CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer by Kai Liu, Tao Ren, Zhangli Lan, Yang Yang, Rong Liu, Yuantong Xu

“…Additionally, the Detailed-Macro Feature Fusion (DMFF) module enables multi-scale feature integration by combining detailed and coarse-grained features, mitigating the significant feature loss encountered during the encoding and decoding stages, and further improving segmentation precision. …”
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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

“…Compared with existing recognition networks and target detection algorithms such as YOLOv7, ResNet50, VGG16, and Swin Transformer, YOLOv10 performs the best in pear leaf recognition in natural scenes. To address the issue of low recognition precision in Yuluxiang, the Spatial and Channel reconstruction Convolution (SCConv) module is introduced on the basis of YOLOv10 to improve the model. …”
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UCrack-DA: A Multi-Scale Unsupervised Domain Adaptation Method for Surface Crack Segmentation by Fei Deng, Shaohui Yang, Bin Wang, Xiujun Dong, Siyuan Tian

“…Additionally, by integrating a Mix-Transformer encoder, a multi-scale dilated attention module, and a mixed convolutional attention decoder, we effectively solve the challenges of cross-domain data distribution differences and complex scene crack segmentation. …”
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SODRS: Semisupervised Learning for One-Stage Small Object Detection in Remote Sensing Images by Mingquan Liu, Lei Kuang, Chengjun Li, Jing Tian, Zifang Chen, Xuewu Han

“…These factors have made it a long-standing technical issue. Traditional object detection methods often perform poorly in this field, especially when dealing with high-resolution remote sensing images, where detection accuracy and robustness fail to meet practical application needs. …”
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Detection of underground personnel safety helmet wearing based on improved YOLOv8n by WANG Qi, XIA Lufei, CHEN Tianming, HAN Hongyin, WANG Liang

“…A convolutional block attention module (CBAM) was integrated into the backbone network to extract key image features and reduce background interference. …”
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PIFRNet: Position Information Guided Feature Reconstruction Network for Salient Object Detection in Remote Sensing Images by Zhen Wang, Ruixiang Li, Xiaotian Wang, Nan Xu, Zhuhong You

“…However, salient object detection for remote sensing images (RSI-SOD) faces unique challenges, including high resolution, diverse object scales, and cluttered backgrounds, which limit the effectiveness of existing methods. To overcome these issues, we propose a Position Information Guided Feature Reconstruction Network, where each module is specifically designed to address a core RSI-SOD challenge. …”
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