EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection by Haojie Chen, Lumei Su, Riben Shu, Tianyou Li, Fan Yin

“…This network integrates feature maps from different levels to detect isolation switches at multiple scales in monitoring scenarios. …”
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Comprehensive Investigation of Machine Learning and Deep Learning Networks for Identifying Multispecies Tomato Insect Images by Chittathuru Himala Praharsha, Alwin Poulose, Chetan Badgujar

“…Extensive experiments were conducted to compare the performance of different optimizers in terms of classification accuracy, convergence speed, and robustness. …”
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Unpaired Spatio-Temporal Fusion for Remote Sensing Images via Deformable Global-Local Feature Alignment by Xinlan Ding, Huihui Song, Xu Zhang

“…Despite the flexibility of the reference, current work with this paradigm suffers from the following issue: due to the relatively long revisit period, drastic changes caused by cloud pollution or floods may occur in different periods. It results in large land cover changes of losing texture details and even semantic category shift (e.g., from the land to the water), which makes it difficult to obtain enough high-quality reference data, leading to severe model degradation. …”
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sEMG-based gesture recognition using multi-stream adaptive CNNs with integrated residual modules by Yutong Xia, Dawei Qiu, Cheng Zhang, Jing Liu

“…IntroductionConvolutional neural networks are widely used in gesture recognition research, which employs surface electromyography. …”
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A regional site response analysis of the Petobo area after the 2018.09.28 Palu–Donggala Indonesia earthquake using an equivalent-linear model by Rini Kusumawardani, Muhsiung Chang, Togani Cahyadi Upomo, Fernando Lopez-Caballero, Dadang Permana

“…The amplification of the bedrock motion on the Petobo surface was more serious than that on the Balaroa surface, which appears to be due to the differences in the subsurface stratification and material properties of the two sites. …”
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Anterior Cruciate Ligament (ACL) Tear Detection Using Hybrid CNN Transformer by Suthir Sriram, Deependra K. Singh, D. V. Sairam, Nivethitha Vijayaraj, Thangavel Murugan

“…However, this also poses some difficulties due to differences in formats of medical images and standard images. …”
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A lip reading method based on adaptive pooling attention Transformer by YAO Yun, HU Zhenxiao, DENG Tao, WANG Xiao

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The lip reading method based on Adaptive Pooling Attention Transformer by YAO Yun, HU Zhenxiao, DENG Tao, WANG Xiao

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Restoration of Out-of-Focus Fluorescence Microscopy Images Using Learning-Based Depth-Variant Deconvolution by Da He, De Cai, Jiasheng Zhou, Jiajia Luo, Sung-Liang Chen

“…As for a wide-field image, there exist different DV-PSFs within the two-dimensional fluorescence image due to the surface undulation. …”
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Augmented self attention network for liver tumour segmentation of CT images by Bilga Jacob, R.S Vinod Kumar, S.S. Kumar

“…The architecture achieved a higher level of Dice score (DSC) – 0.923, Intersection-Over-Union (IoU) – 0.913, Volumetric Overlap Error (VOE) – 0.086 and Relative Volume Difference (RVD) – 3.85 for liver tumour segmentation which is remarkable.…”
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State of Health Prediction for Lithium-Ion Batteries Based on Gated Temporal Network Assisted by Improved Grasshopper Optimization by Xiankun Wei, Silun Peng, Mingli Mo

“…However, novel algorithms are still needed because few studies have considered the correlations between monitored parameters in Euclidean space and non-Euclidean space at different time points. To address this challenge, a novel gated-temporal network assisted by improved grasshopper optimization (IGOA-GGNN-TCN) is developed. …”
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Autonomous Extraction Technology for Aquaculture Ponds in Complex Geological Environments Based on Multispectral Feature Fusion of Medium-Resolution Remote Sensing Imagery by Zunxun Liang, Fangxiong Wang, Jianfeng Zhu, Peng Li, Fuding Xie, Yifei Zhao

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Temporal Enhancement of Top-N Recommendation on Heterogeneous Graphs by Feng Hu, Jun Lin

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Fourier Neural Operator Networks for Solving Reaction–Diffusion Equations by Yaobin Hao, Fangying Song

“…Next, we conducted experiments on the number of convolutional layers. The results showed that the performance of the models did not differ significantly when using two, three, or four layers, with the performance of two or three layers even slightly surpassing that of four layers. …”
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A Capsule Decision Neural Network Based on Transfer Learning for EEG Signal Classification by Wei Zhang, Xianlun Tang, Xiaoyuan Dang, Mengzhou Wang

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GPR-Based Leakage Reconstruction of Shallow-Buried Water Supply Pipelines Using an Improved UNet++ Network by Qingqi Xu, Qinghua Liu, Shan Ouyang

“…The network employs an encoder–decoder architecture, in which the encoder incorporates multi-scale directional convolutions with coordinate attention to extract and compress features across different scales effectively. …”
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Prediction and Parameter Optimization of Surface Settlement Induced by Shield Tunneling Using Improved Informer Algorithm by Shisen Zhao, Xianda Feng, Kefeng Peng

“…The improved Informer algorithm exhibited significant enhancements in prediction accuracy, perception range across different timescales, and computational efficiency. …”
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Remote Sensing Image-Based Building Change Detection: A Case Study of the Qinling Mountains in China by Lei Fu, Yunfeng Zhang, Keyun Zhao, Lulu Zhang, Ying Li, Changjing Shang, Qiang Shen

“…With the widespread application of deep learning in Earth observation, remote sensing image-based building change detection has achieved numerous groundbreaking advancements. However, differences across time periods caused by temporal variations in land cover, as well as the complex spatial structures in remote sensing scenes, significantly constrain the performance of change detection. …”
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A Comprehensive Review on Unsupervised Domain Adaptation for 3D Segmentation and Reconstruction in CT Urography Imaging by Shreya, Sushanth, Dasharathraj K. Shetty, Shreepathy Ranga Bhatta, Nikita Panwar

“…The most important part of this review is the discussion on 3D kidney segmentation and reconstruction from urographic images, which has helped doctors a lot with the accurate diagnosis and planning of treatment for kidney diseases. Even though 3D convolution networks have been used a lot in medical picture segmentation, it can be hard to adapt them to clinical data from different modalities that have not been seen before. …”
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Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Netwo... by Han Qiu, Rong Hu, Jiaqing Chen, Zihao Yuan

“…A series of simpler intrinsic mode functions (IMFs) with different frequency characteristics can be decomposed by CEEMDAN from data, then each IMF is reconstructed based on calculating the sample entropy of each IMF. …”
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