RPFusionNet: An Efficient Semantic Segmentation Method for Large-Scale Remote Sensing Images via Parallel Region–Patch Fusion by Shiyan Pang, Weimin Zeng, Yepeng Shi, Zhiqi Zuo, Kejiang Xiao, Yujun Wu

“…Mainstream deep learning segmentation models are designed for small-sized images, and when applied to high-resolution remote sensing images, the limited information contained in small-sized images greatly restricts a model’s ability to capture complex contextual information at a global scale. …”
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A Spatiotemporal U-Net-Based Data Preprocessing Pipeline for Sun-Synchronous Path Planning in Lunar South Polar Exploration by Yang Chen, Guangfei Wei, Hao Zhang, Jianfeng Lu, Fuchuan Pang

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DeepBiteNet: A Lightweight Ensemble Framework for Multiclass Bug Bite Classification Using Image-Based Deep Learning by Doston Khasanov, Halimjon Khujamatov, Muksimova Shakhnoza, Mirjamol Abdullaev, Temur Toshtemirov, Shahzoda Anarova, Cheolwon Lee, Heung-Seok Jeon

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GreenNet: A dual-encoder network for urban green space classification using high-resolution remotely sensed images by Ke Chen, Yang Wang, Cunrui Huang, Jing Wang, Sabrina L. Li, Haiyan Guan, Lingfei Ma

“…To address these issues, this paper presents a novel dual-encoder network, termed GreenNet, specifically designed for urban green space classification from high-resolution remotely sensed images. …”
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Evaluation of Time Delay and Cumulative Effects of Meteorological Drought on Net Primary Productivity of Vegetation in the Upper Reaches of the Yellow River, China by Huazhu Xue, Zhi Li, Guotao Dong, Hao Wang

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BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers by Cheng Lv, Xu-Jun Shu, Xu-Jun Shu, Quan Liang, Jun Qiu, Zi-Cheng Xiong, Jing bo Ye, Shang bo Li, Cheng Qing Liu, Jing Zhen Niu, Sheng-Bo Chen, Hong Rao

“…Five-fold cross-validation was employed for result verification.ResultsIn the test set evaluation, BrainTumNet achieved an Intersection over Union (IoU) of 0.921, Hausdorff Distance (HD) of 12.13, and Dice Similarity Coefficient (DSC) of 0.91 for tumor segmentation. …”
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Mf-net: multi-feature fusion network based on two-stream extraction and multi-scale enhancement for face forgery detection by Hanxian Duan, Qian Jiang, Xin Jin, Michal Wozniak, Yi Zhao, Liwen Wu, Shaowen Yao, Wei Zhou

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RDSF-Net: Residual Wavelet Mamba-Based Differential Completion and Spatio-Frequency Extraction Remote Sensing Change Detection Network by Shuo Wang, Dapeng Cheng, Genji Yuan, Jinjiang Li

“…The network is designed with residual wavelet transform as the downsampler, which effectively integrates the key directional information and the overall structural information in the original features, and uses convolutional neural network and Mamba as the backbone network for both long-range and short-range feature extraction. …”
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EDT-Net: A Lightweight Tunnel Water Leakage Detection Network Based on LiDAR Point Clouds Intensity Images by Zhenyu Liu, Xianjun Gao, Yuanwei Yang, Lei Xu, Shaoning Wang, Ningsheng Chen, Zhiwei Wang, Yuan Kou

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Approach for identifying crop seeds with similar appearances using hyperspectral images and improved ResNet 18 based on cloud platform by Hui Li, Xuliang Duan

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Railway Tracks Extraction from High Resolution Unmanned Aerial Vehicle Images Using Improved NL-LinkNet Network by Jing Wang, Xiwei Fan, Yunlong Zhang, Xuefei Zhang, Zhijie Zhang, Wenyu Nie, Yuanmeng Qi, Nan Zhang

“…To address these challenges, this paper introduces an improved NL-LinkNet network, named NL-LinkNet-SSR, designed specifically for railway track detection. …”
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FibroRegNet: A Regression Framework for the Pulmonary Fibrosis Prognosis Prediction Using a Convolutional Spatial Transformer Network by Pardhasaradhi Mittapalli, V. Thanikaiselvan

“…FibroRegNet is designed to acquire knowledge through the regression function which maps the multimodal inputs, including CT scan and demographic information, to the coefficients of the quadratic polynomial ridge regression of FVC as outputs. …”
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Long Lasting Insecticide-Treated Nets Utilization and Associated Factors Among Pregnant Women in Shebel Berenta District, Northwest Ethiopia by Yeshitla Getnet, Abraham Teym, Moges Wubie, Sintayehu Shiferaw, Bayou Tilahun Assaye, Zelalem Aneley, Habitamu Mekonen Abera, Habtamu Temesgen

“…Attending antenatal care, receiving information (messages) about malaria and long lasting insecticide-treated net, and mother’s being literate had a substantial impact on long lasting insecticide-treated net utilization. …”
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A study of user satisfaction and net benefits in indonesia through the DeLone and McLean Model for E-Government success by Rahmatullah Rahmatullah, Akhmad Habibi, Khaeruddin Khaeruddin, Lalu Nurul Yaqin, Turki Mesfer Alharmali, Mohd Sofian Omar Fauzee, Jazihan Mahat

“…Nine hypotheses were included to test the relationships among variables (information quality, service quality, system quality, behavioral intention, user satisfaction, and net benefits). …”
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Multi-Level Feature Fusion in CNN-Based Human Action Recognition: A Case Study on EfficientNet-B7 by Pitiwat Lueangwitchajaroen, Sitapa Watcharapinchai, Worawit Tepsan, Sorn Sooksatra

“…A simple approach to enhance model performance is incorporating additional data modalities, such as depth frames, point clouds, and skeleton information, while previous studies have predominantly used late fusion techniques to combine these modalities, our research introduces a multi-level fusion approach that combines information at early, intermediate, and late stages together. …”
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A Field Trial to Study the Effects of <i>Stenella attenuata</i> Deterrent on the Catch of a Light-Falling Net Fishery by Teng Wang, Jie Li, Lei Yan, Bin Xie, Peng Zhang, Zhongchang Song, Min Li, Weijie Fu, Yu Zhang

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FUSE-Net: Multi-Scale CNN for NIR Band Prediction from RGB Using GNDVI-Guided Green Channel Enhancement by Gwanghyeong Lee, Deepak Ghimire, Donghoon Kim, Sewoon Cho, Byoungjun Kim, Sunghwan Jeong

“…Through ablation studies and band combination analysis, we assessed the model’s ability to recover spectral information. The experimental results showed that the G-RGB input consistently outperformed unmodified RGB across multiple metrics, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), spectral correlation coefficient (SCC), and structural similarity (SSIM), with the best performance observed when paired with FUSE-Net. …”
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Skin lesion segmentation with a multiscale input fusion U-Net incorporating Res2-SE and pyramid dilated convolution by Zhihui Liu, Jie Hu, Xulu Gong, Fuzhong Li

“…The MIF module processes lesions of different sizes and morphologies by fusing input information from various scales. The Res2-SE module integrates Res2Net and SE mechanisms to enhance multi-scale feature extraction. …”
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Robust Bi-CBMSegNet framework for advancing breast mass segmentation in mammography with a dual module encoder-decoder approach by Yu Wang, Mudassar Ali, Tariq Mahmood, Amjad Rehman, Tanzila Saba

“…Bi-CBMSegNet employs an advanced encoder-decoder architecture comprising two distinct modules: the Global Feature Enhancement Module (GFEM) and the Local Feature Enhancement Module (LFEM). …”
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YOLO-SegNet: A Method for Individual Street Tree Segmentation Based on the Improved YOLOv8 and the SegFormer Network by Tingting Yang, Suyin Zhou, Aijun Xu, Junhua Ye, Jianxin Yin

“…Therefore, this paper, based on a large, publicly available urban street tree dataset, proposes YOLO-SegNet for individual street tree segmentation. In the first stage of the street tree object detection task, the BiFormer attention mechanism was introduced into the YOLOv8 network to increase the contextual information extraction and improve the ability of the network to detect multiscale and multishaped targets. …”
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