Re-Parameterization After Pruning: Lightweight Algorithm Based on UAV Remote Sensing Target Detection by Yang Yang, Pinde Song, Yongchao Wang, Lijia Cao

“…However, UAV remote sensing requires target detection algorithms to have higher inference speeds and greater accuracy in detection. At present, most lightweight object detection algorithms have achieved fast inference speed, but their detection precision is not satisfactory. …”
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Boundary aware microscopic hyperspectral pathology image segmentation network guided by information entropy weight by Xueying Cao, Hongmin Gao, Ting Qin, Min Zhu, Ping Zhang, Ping Zhang, Peipei Xu, Peipei Xu

“…Finally, we propose a multi-scale spatial boundary feature extraction block to guide the model in emphasizing the most important spatial locations and boundary regions.ResultWe evaluate BE-Net on medical microscopic hyperspectral pathological image datasets of gastric intraepithelial neoplasia and gastric mucosal intestinal metaplasia. …”
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Enhanced Panoramic Radiograph-Based Tooth Segmentation and Identification Using an Attention Gate-Based Encoder–Decoder Network by Salih Taha Alperen Özçelik, Hüseyin Üzen, Abdulkadir Şengür, Hüseyin Fırat, Muammer Türkoğlu, Adalet Çelebi, Sema Gül, Nebras M. Sobahi

“…Background: Dental disorders are one of the most important health problems, affecting billions of people all over the world. …”
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AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view by Mostafa Jalilifar, Mahdi Sadeghi, Alireza Emami-Ardekani, Ahmad Bitarafan-Rajabi, Kouhyar Geravand, Parham Geramifar

“…Four AI algorithms- multilayer perceptron (MLP), linear regression, support vector regression model, decision tree, convolution neural network, and U-Net were used for dose estimation. …”
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Velocity Model Construction and Time-to-Depth Conversion of a Vintage Seismic Reflection Profile for Improving the Constraints on a Subsurface Geological Model: An Example from the... by Aasiya Qadir, Nicolò Chizzini, Mariagiada Maiorana, Andrea Artoni, Luigi Torelli, Attilio Sulli

“…This was followed by the Gaussian convolution operator and a data exclusion filter to improve the accuracy of the velocity model. …”
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Efficient and Effective NDVI Time-Series Reconstruction by Combining Deep Learning and Tensor Completion by Ang Li, Menghui Jiang, Dong Chu, Xiaobin Guan, Jie Li, Huanfeng Shen

“…Considering the temporal continuity and spatial correlation of NDVI time-series data, we combine long short-term memory with a convolution (LSTM-Conv) structure and utilize residual learning and dense connection strategies to mine the spatiotemporal features in depth. …”
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A Deep Learning Approach for Crop Disease and Pest Classification Using Swin Transformer and Dual-Attention Multi-Scale Fusion Network by R. Karthik, Armaano Ajay, Akshaj Singh Bisht, T. Illakiya, K. Suganthi

“…Current diagnostic methods are mostly manual, which is time-consuming and requires domain expertise. …”
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Deep Learning-Based Ground-Penetrating Radar Inversion for Tree Roots in Heterogeneous Soil by Xibei Li, Xi Cheng, Yunjie Zhao, Binbin Xiang, Taihong Zhang

“…Additionally, a GPR simulation data set and a measured data set are built in this study, which were used to train inversion models and validate the effectiveness of GPR inversion methods.The introduced GPR inversion model is a pyramid convolutional network with vision transformer and edge inversion auxiliary task (PyViTENet), which combines pyramidal convolution and vision transformer to improve the diversity and accuracy of data feature extraction. …”
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Spatial-Temporal Semantic Feature Interaction Network for Semantic Change Detection in Remote Sensing Images by Yuhang Zhang, Wuxia Zhang, Songtao Ding, Siyuan Wu, Xiaoqiang Lu

“…The “from-to” information of the acquired image has more profound practical significance than Binary Change Detection (BCD). However, most deep learning-based SCD algorithms do not fully exploit the spatial-temporal information of multilevel features, leading to challenges in extracting LCLU features in complex scenes. …”
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Feature Interaction and Adaptive Fusion Network With Spectral Modulation for Pansharpening by Lihua Jian, Jiabo Liu, Lihui Chen, Di Zhang, Gemine Vivone, Xichuan Zhou

“…In addition, a residual structure-based self-guided spatial-channel adaptive convolution is introduced to accommodate diverse features within FASA adaptively. …”
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Investigation of ensembles of deep learning models for improved chronic kidney diseases detection in CT scan images by I.I. Ayogu, C.F. Daniel, B.A. Ayogu, J.N. Odii, C.L. Okpalla, E.C. Nwokorie

“…In general, nonetheless, kidney stone was the most difficult disease to detect for all the models investigated. …”
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GANFlow: A Hybrid Model for SAR Image Target Open-Set Recognition Based on GAN and the Flow-Based Module by Jikai Qin, Jiusheng Han, Zheng Liu, Lei Ran, Rong Xie, Tat-Soon Yeo

“…Most synthetic aperture radar (SAR) automatic target recognition (ATR) methods can achieve good recognition results only under the closed-set assumption. …”
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Detection of Masses in Mammogram Images Based on the Enhanced RetinaNet Network With INbreast Dataset by Wang M, Liu R, Luttrell IV J, Zhang C, Xie J

“…Specifically, we introduced a novel modification to the network structure, where the feature map M5 is processed by the ReLU function prior to the original convolution kernel. This strategic adjustment was designed to prevent the loss of resolution for small mass features. …”
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An Accelerated FPGA-Based Parallel CNN-LSTM Computing Device by Xin Zhou, Wei Xie, Han Zhou, Yongjing Cheng, Ximing Wang, Yun Ren, Shandong Yuan, Liuwen Li

“…Most of these studies connect LSTM networks behind CNNs. …”
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Learning Domain Generalized Remote Sensing Image Segmentation by Multiscale Instance Disentanglement by Jie Luo, Tianwen Luo, Maoyang Wang, Linyi Li, Wen Zhang, Lingkui Meng

“…Rapid development has been made in the past decade owing to the deep learning techniques. Most of the existing methods assume that the training and inference remote sensing images hold the identical and independent distribution. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…Implementing traditional OPF algorithms can be challenging for large-scale networks with complex topologies and constraints. The most recent advancement in learning-based models has shifted the paradigm towards data-driven approaches. …”
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A Lightweight Method for Detecting Bearing Surface Defects Based on Deep Learning and Ontological Reasoning by Xiaolin Shi, Haisong Xu, Han Zhang, Yi Li, Xinshuo Li, Fan Yang

“…First, the dynamic convolution is fused with the Ghost module and the combined structure is embedded into the C3 module, thus constructing a new module named C3-GhostDynamicConv (C3-GDConv) module, which achieves network lightweighting while maintaining efficient computation. …”
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DAU-YOLO: A Lightweight and Effective Method for Small Object Detection in UAV Images by Zeyu Wan, Yizhou Lan, Zhuodong Xu, Ke Shang, Feizhou Zhang

“…To maintain an extremely lightweight architecture, the bottom-most Bottom–Up layer is removed, reducing model complexity without compromising detection accuracy. …”
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Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening by Yanjie Sun, Xiaolong Song, Zhi Li, Haijue Xu, Yuchuan Bai

“…Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. …”
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Combined influence of quantum iterative reconstruction level and kernel sharpness on image quality in photon counting CT angiography of the upper leg by Kristina Krompaß, Florian Andreas Goldbrunner, Viktor Hartung, Süleyman Ergün, Dominik Peter, Robin Hendel, Henner Huflage, Theresa Sophie Patzer, Jan-Lucca Hennes, Thorsten Alexander Bley, Jan-Peter Grunz, Philipp Gruschwitz

“…Sharp kernels benefited most from noise reduction of higher QIR levels in lower extremity PCD-CTA. …”
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