Deep Learning with 3D ResNets for Comprehensive Dual-Lane Speed Climbing Video Analysis by Xie Y., Mariano V.

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DE-Unet: Dual-Encoder U-Net for Ultra-High Resolution Remote Sensing Image Segmentation by Ye Liu, Shitao Song, Miaohui Wang, Hao Gao, Jun Liu

“…Our method incorporates dual encoders into the symmetrical framework of U-Net. The dual encoders endow the network with strong global and local perception capabilities simultaneously, while the U-Net's symmetrical structure guarantees the network's robust decoding ability. …”
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TWD-DepNet: a deep network enhanced by three-way decisions for EEG-based depression detection by Chunlei Shi, Shouzhu Yan, Wei He, Haiyan Wang

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The Role of VADER and SentiWordNet Labeling in Naïve Bayes Accuracy for Sentiment Analysis of Rice Price Increases by Ihtiar Nur Furqon, Dewi Soyusiawaty

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NMD-FusionNet: a multimodal fusion-based medical imaging-assisted diagnostic model for liver cancer by Qing Ye, Minghao Luo, Jing Zhou, Chunlei Cheng, Lin Peng, Jia Wu

“…To address these challenges, this study proposes NMD-FusionNet, a deep learning-based framework for liver cancer image segmentation and diagnosis. …”
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Artificial Intelligence Model Assists Knee Osteoarthritis Diagnosis via Determination of K-L Grade by Joo Chan Choi, Min Young Jeong, Young Jae Kim, Kwang Gi Kim

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RS-FeatFuseNet: An Integrated Remote Sensing Object Detection Model with Enhanced Feature Extraction by Yijuan Qiu, Jiefeng Xue, Gang Zhang, Xuying Hao, Tao Lei, Ping Jiang

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LTR-Net: A deep learning-based approach for financial data prediction and risk evaluation in enterprises. by Shimiao Liu

“…LTR-Net effectively processes the multi-dimensional features and dynamic changes in financial data by incorporating a temporal dependency modeling module, a global information capture module, and a deep feature extraction module. …”
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EF-net: Accurate edge segmentation for segmenting COVID-19 lung infections from CT images by Wenjin Zhong, Hanwen Zhang

“…This study introduces a novel model called the edge-based dual-parallel attention (EDA)-guided feature-filtering network (EF-Net), specifically designed to accurately segment the edges of COVID-19 lesions. …”
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Fine-grained image classification using the MogaNet network and a multi-level gating mechanism by Dahai Li, Su Chen

“…A feature extraction network based on MogaNet is constructed, and multi-scale feature fusion is combined to fully mine image information. …”
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An Efficient Fine-Grained Recognition Method Enhanced by Res2Net Based on Dynamic Sparse Attention by Qifeng Niu, Hui Wang, Feng Xu

“…This paper presents an efficient architecture built upon the Res2Net backbone, significantly enhanced by a dynamic Sparse Attention mechanism. …”
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SAD-Net: a full spectral self-attention detail enhancement network for single image dehazing by Qingjun Niu, Kun Wu, Jialu Zhang, Zhenqi Han, Lizhuang Liu

“…However, existing dehazing methods using vanilla convolution only extract features in the temporal domain and lack the ability to capture multi-directional information. To address the aforementioned issues, we design a new full spectral attention-based detail enhancement dehazing network, named SAD-Net. …”
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MCAF-Net: Multi-Channel Temporal Cross-Attention Network with Dynamic Gating for Sleep Stage Classification by Xuegang Xu, Quan Wang, Changyuan Wang, Yaxin Zhang

“…Experimental results show that our proposed method successfully integrates information from multiple channels, achieving significant improvements in sleep stage classification compared to the vast majority of existing methods.…”
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Quantifying the Contribution of Extreme Climate Indices to the Dynamics of Net Primary Productivity of Vegetation in the Qinba Mountain Area by HAO Chengyuan, ZENG Qiuqiang

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MANS-Net: Multiple Attention-Based Nuclei Segmentation in Multi Organ Digital Cancer Histopathology Images by Ibtihaj Ahmad, Zain Ul Islam, Saleem Riaz, Fuzhong Xue

“…We report that MANS-Net significantly outperforms state-of-the-art segmentation algorithms. …”
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MSD-Net: Multi-scale dense convolutional neural network for photoacoustic image reconstruction with sparse data by Liangjie Wang, Yi-Chao Meng, Yiming Qian

“…MSD-Net exploits the advantages of multi-scale information fusion and dense connections to improve the performance of CNN. …”
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Seismic Damage Quantification of RC Short Columns from Crack Images Using the Enhanced U-Net by Zixiao Chen, Qian Chen, Zexu Dai, Chenghao Song, Xiaobin Hu

“…The results demonstrate that it has better accuracy in terms of recognizing tiny cracks compared to the original U-Net. By image analysis, the crack information was further extracted from the crack images to investigate the damage development of RC short columns. …”
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LS-MambaNet: Integrating Large Strip Convolution and Mamba Network for Remote Sensing Object Detection by Lingyu Yan, Zijian He, Zhiqi Zhang, Guangqi Xie

“…To address the above challenges, we propose a new target detection framework for complex remote sensing images, LS-MambaNet. Specifically, firstly, a group fusion strategy is combined with the introduction of large-band convolution to adaptively adjust the receptive domains of the features, which enhances the spatial context information extraction for objects with high aspect ratios. …”
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FEPA-Net: A Building Extraction Network Based on Fusing the Feature Extraction and Position Attention Module by Yuexin Liu, Yulin Duan, Xuya Zhang, Wen Zhang, Chang Wang

“…In this paper, we propose the FEPA-Net network model, which integrates the feature extraction and position attention module for the extraction of buildings in remote sensing images. …”
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SwinLabNet: Jujube Orchard Drivable Area Segmentation Based on Lightweight CNN-Transformer Architecture by Mingxia Liang, Longpeng Ding, Jiangchun Chen, Liming Xu, Xinjie Wang, Jingbin Li, Hongfei Yang

“…This approach optimized feature extraction and contextual information capture, effectively addressing long-range dependencies, global information acquisition, and detailed boundary processing. …”
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