BrainNet: an automated approach for brain stress prediction utilizing electrodermal activity signal with XLNet model by Liao Xuanzhi, Abeer Hakeem, Linda Mohaisen, Muhammad Umer, Muhammad Attique Khan, Shrooq Alsenan, Shtwai Alsubai, Nisreen Innab

“…This burgeoning field aims to provide accurate information and prediction about individuals' stress levels by analyzing behavioral data and physiological signals. …”
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C2F-Net: Coarse-to-Fine Multidrone Collaborative Perception Network for Object Trajectory Prediction by Mingxin Chen, Zhirui Wang, Zhechao Wang, Liangjin Zhao, Peirui Cheng, Hongqi Wang

“…Existing collaborative perception methods struggle to address the nonuniform spatial distribution of targets and the spatial heterogeneity of multisource perception information typical in remote sensing scenarios. To tackle these challenges, we propose a coarse-to-fine feature fusion network C2F-Net, utilizing coarse-grained information interaction to guide the fusion of fine-grained features. …”
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PZS‐Net: Incorporating of Frame Sequence and Multi‐Scale Priors for Prostate Zonal Segmentation in Transrectal Ultrasound by Jianguo Ju, Qian Zhang, Pengfei Xu, Tiange Liu, Cheng Li, Ziyu Guan

“…To overcome the limitation, a novel Prostate Zonal Segmentation Network (PZS‐Net), based on U‐Net, which learns critical cross‐frame information and multi‐scale features from sequential frames, is proposed. …”
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MMPW-Net: Detection of Tiny Objects in Aerial Imagery Using Mixed Minimum Point-Wasserstein Distance by Nan Su, Zilong Zhao, Yiming Yan, Jinpeng Wang, Wanxuan Lu, Hongbo Cui, Yunfei Qu, Shou Feng, Chunhui Zhao

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MDEU-Net: Medical Image Segmentation Network Based on Multi-Head Multi-Scale Cross-Axis by Shengxian Yan, Yuyang Lei, Jing Zhang, Xiao Gao, Xiang Li, Penghui Wang, Hui Cao

“…The proposed architecture enables the model to focus on both local and global information while capturing features at various spatial scales. …”
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Rotten strawberry classification based on EfficientNet V2 algorithm fused with GCN and CA-Transformer by WANG Wei, YANG Shizhong, GONG Yucheng, GAO Sheng, DENG Zhaopeng

“…Firstly, a graph convolution branch was added to the baseline model, which updated feature representations by aggregating the surrounding information of nodes, better capturing the contextual information of nodes in the graph structure. …”
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DAF-Net: Dual-Aperture Feature Fusion Network for Aircraft Detection on Complex-Valued SAR Image by Qingbiao Meng, Youming Wu, Yuxi Suo, Tian Miao, Qingyang Ke, Xin Gao, Xian Sun

“…Considering the aforementioned challenges, for targets exhibiting anisotropy and dispersion under high resolution, their nonstationary characteristics can be extracted by decomposing subapertures and employed as additional information to enhance detection accuracy. Therefore, we propose a dual-aperture feature fusion network (DAF-Net) designed to improve aircraft detection by mining, enhancing, and fusing features from both full-aperture and subaperture images. …”
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Kidney Ensemble-Net: Enhancing Renal Carcinoma Detection Through Probabilistic Feature Selection and Ensemble Learning by Zaib Akram, Kashif Munir, Muhammad Usama Tanveer, Atiq Ur Rehman, Amine Bermak

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PneuX-Net: An Enhanced Feature Extraction and Transformation Approach for Pneumonia Detection in X-Ray Images by Kashif Munir, Muhammad Usama Tanveer, Hasan J. Alyamani, Amine Bermak, Atiq Ur Rehman

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A multi-modal deep learning solution for precise pneumonia diagnosis: the PneumoFusion-Net model by Yujie Wang, Yujie Wang, Can Liu, Yinghan Fan, Chenyue Niu, Wanyun Huang, Yixuan Pan, Jingze Li, Jingze Li, Yilin Wang, Jun Li, Jun Li, Jun Li

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Research on Supraharmonic detection in renewable energy grid Inte-gration based on improved ResNet18 by Yangyang Zhu, Fei Zhong, Jiaqi Gao, Yuntai Cao, Xiaotian Wang, Zhihong Jiang

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RHCrackNet: Refined Hierarchical Feature Fusion and Enhancement Network for Pixel-Level Pavement Anomaly Detection by Wenjing Liu, Zhenhua Li, Ji Wang, Qingjie Lu

“…While existing Convolutional Neural Network (CNN) approaches have achieved high performance, their robustness to texture noise is limited, and the completeness of detected pixel-level cracks remains uncertain due to insufficient extraction of contextual information. To address these limitations, we propose a novel pavement anomaly detection network called RHCrackNet. …”
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MSaD-Net: A Mix Self-Attention Networks for 3D Point Cloud Denoising by Xusheng Zhu, Shuai Ma, Daixin Chen, Li Zhou, Haibo Tang

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MSA-Net: multiple self-attention mechanism for 3D lung nodule classification in CT images by Jiating Pan, Lishi Liang, Peng Sun, Yongbo Liang, Jianming Zhu, Zhencheng Chen

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HRT-Net: A Cell-free Cooperative Sensing Method Based on Attention-weighted Hierarchical Network by Shengheng LIU, He YAN, Xingkang LI, Dazhuan XU, Dongming WANG, Yongming HUANG

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DWTMA-Net: Discrete Wavelet Transform and Multi-Dimensional Attention Network for Remote Sensing Image Dehazing by Xin Guan, Runxu He, Le Wang, Hao Zhou, Yun Liu, Hailing Xiong

“…To address these issues, we propose a novel network called DWTMA-Net that integrates discrete wavelet transform with multi-dimensional attention, aiming to restore image information in both the frequency and spatial domains to enhance overall image quality. …”
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ANF-Net: A Refined Segmentation Network for Road Scenes with Multiple Noises and Various Morphologies of Cracks by Xiao Hu, Qihao Chen, Xiuguo Liu, Gang Deng, Cheng Chi, Bin Wang

“…To address these issues, this paper proposes a refined pixel-level segmentation network (ANF-Net) suitable for complex crack detection scenarios with high noise levels and diverse crack morphologies. …”
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IUR-Net: A Multi-Stage Framework for Label Refinement Tasks in Noisy Remote Sensing Samples by Yibing Xiong, Xiangyun Hu, Xin Geng, Lizhen Lei, Aokun Liang

“…IUR-Net leverages newly acquired remote sensing images and their corresponding noisy labels to automatically identify erroneous regions, update them with more accurate information, and refine the results to improve label quality. …”
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Enhancing the Ground Truth Disparity by MAP Estimation for Developing a Neural-Net Based Stereoscopic Camera by Hanbit Gil, Sehyun Ryu, Sungmin Woo

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RAMAS-Net: a module-optimized convolutional network model for aortic valve stenosis recognition in echocardiography by Yejia Gan, Wanzhong Huang, Yan Deng, Xiaoying Xie, Yuanyuan Gu, Yaozhuang Zhou, Qian Zhang, Maosheng Zhang, Yangchun Liu

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