Multiple orbital angular momentum modes conversion with transmission metasurface by Sitong He, Qiang Feng, Qingle Tu, Haixia Liu, Jiaqi Han, Yan Shi, Long Li

“…The orthogonal properties between different orbital angular momentum (OAM) modes of vortex beams have made it a great potential research area in recent years. …”
Get full text

Automatic Disease Detection from Strawberry Leaf Based on Improved YOLOv8 by Yuelong He, Yunfeng Peng, Chuyong Wei, Yuda Zheng, Changcai Yang, Tengyue Zou

“…Furthermore, a parameter-sharing diverse branch block (DBB) sharing head is constructed to improve the model’s target processing ability at different spatial scales and increase its accuracy without adding too much calculation. …”
Get full text

AI-enhanced real-time monitoring of marine pollution: part 1-A state-of-the-art and scoping review by Navya Prakash, Navya Prakash, Oliver Zielinski, Oliver Zielinski

“…This review synthesizes 53 recent studies on Artificial Intelligence applications in marine pollution detection, focusing on different model architectures, sensing technologies and preprocessing methods. …”
Get full text

Facial Feature Extraction Algorithm Based on Improved YOLOv7-Tiny by Yining Yao, Yawen Wang, Changyuan Wang, Yibo Zhang, Tingting Liu, Gaofeng Wang

“…The algorithm employs depthwise-separable convolution combined with spatial depth convolution to effectively extract key facial features. …”
Get full text

LPFFNet: Lightweight Prior Feature Fusion Network for SAR Ship Detection by Xiaozhen Ren, Peiyuan Zhou, Xiaqiong Fan, Chengguo Feng, Peng Li

“…In addition, the enhanced ghost convolution (EGConv) is used to generate more reliable gradient information. …”
Get full text

Neural Network-Based Analysis of Forest Fire Aftermath in Class-Imbalanced Remote Sensing Earth Image Classification by V. Hnatushenko, V. Hnatushenko, V. Hnatushenko, D. Soldatenko

“…To illustrate our method, we use Sentinel-2 remote sensing (RS) images covering a number of regions in Ukraine, and then we create an image dataset of the region and for training and testing make data augmentation. The models with different architectural features were investigated.…”
Get full text

Outdoor Dataset for Flying a UAV at an Appropriate Altitude by Theyab Alotaibi, Kamal Jambi, Maher Khemakhem, Fathy Eassa, Farid Bourennani

“…Eleven experiments performed with the Gazebo simulator using a drone and a convolution neural network (CNN) proved the database’s effectiveness in avoiding different types of obstacles while maintaining an appropriate altitude and the drone’s ability to navigate in a 3D environment.…”
Get full text

An applied noise model for scintillation-based CCD detectors in transmission electron microscopy by Christian Zietlow, Jörg K. N. Lindner

“…Thus, this paper aims to give an insight into the different noise contributions occurring on such detectors, into their underlying statistics and their correlation. …”
Get full text

Crack Detection and Evolution Law for Rock Mass under SHPB Impact Tests by Xie Beijing, Dihao Ai, Yu Yang

“…Secondly, a deep convolution network model named CrackSHPB was designed based on a deep learning algorithm. …”
Get full text

Comparative Analysis of Hybrid Deep Learning Models for Electricity Load Forecasting During Extreme Weather by Altan Unlu, Malaquias Peña

“…This research is divided into two case studies that analyze different combined DL model architectures. Case Study 1 conducts CNN-Recurrent (RNN, LSTM, GRU, BiRNN, BiGRU, and BiLSTM) models with fully connected dense layers, which combine convolution and recurrent neural networks to capture both spatial and temporal dependencies in the data. …”
Get full text

Tuberculosis detection with customized CNN and oversampling techniques: a deep learning approach by B. H. Shekar, Shazia Mannan

“…To deal with the issue of unbalanced classes in the TB CXR dataset, we use different oversampling techniques such as weighted averaging, SMOTE, ADASYN and Borderline SMOTE. …”
Get full text

YOLO-SWD—An Improved Ship Recognition Algorithm for Feature Occlusion Scenarios by Ruyan Zhou, Mingkang Gu, Haiyan Pan

“…YOLOv11 possesses stronger feature extraction capabilities and its multi-branch structure effectively captures features of targets at different scales. Three improved modules are introduced: the DLKA module enhances the perception of local details and global context through dynamic deformable convolution and large receptive field attention mechanisms; the CKSP module improves the model’s ability to extract target boundaries and shapes; and the WTHead enhances the diversity and robustness of feature extraction. …”
Get full text

SuperEdgeGO: Edge-supervised graph representation learning for enhanced protein function prediction. by Shugang Zhang, Yuntong Li, Wenjian Ma, Qing Cai, Jing Qin, Xiangpeng Bi, Huasen Jiang, Xiaoyu Huang, Zhiqiang Wei

“…In this article, we propose SuperEdgeGO, which introduces the supervision of edges in protein graphs to learn a better graph representation for protein function prediction. Different from common graph convolution methods that uses edge information in a plain or unsupervised way, we introduce a supervised attention to encode the residue contacts explicitly into the protein representation. …”
Get full text

Post-disaster flooded region segmentation using DeepLabv3+ and unmanned aerial system imagery by Akila Agnes Sundaresan, Appadurai Arun Solomon

“…To evaluate its performance, the study experiments with various backbone architectures, including ResNet-18, ResNet-50, MobileNetV2, and Xception, under different configurations of downsampling rates (8 and 16) and atrous rates (8, 12, and 16). …”
Get full text

Research on the Real-Time Scoring of Chest Ring Target Based on Transfer Learning and Improved Lightweight Neural Network by Minghui Meng, Chuande Zhou

“…Then, grouped shuffle convolution (GSConv) is used to reconstruct the standard down sampling convolutions in the PANFPN structure, promoting feature information extraction and fusion at bullet hole edges, reducing model computational complexity, and maintaining detection accuracy. …”
Get full text

An AI-Based Horticultural Plant Fruit Visual Detection Algorithm for Apple Fruits by Bin Yan, Xiameng Li, Rongshan Yan

“…The Depthwise Separable Convolution (DWConv) module has many advantages: (1) It has high computational efficiency, reducing the number of parameters and calculations in the model; (2) It makes the model lightweight and easy to deploy in hardware; (3) DWConv can be combined with other modules to enhance the multi-scale feature extraction capability of the detection network and improve the ability to capture multi-scale information; (4) It balances the detection accuracy and speed of the model; (5) DWConv can flexibly adapt to different network structures. …”
Get full text

Multitask semantic change detection guided by spatiotemporal semantic interaction by Yinqing Wang, Liangjun Zhao, Yueming Hu, Hui Dai, Yuanyang Zhang

“…To further enhance detection performance, a dynamic depthwise separable convolution is designed in the CTIM module, which can adaptively adjust convolution kernels to more precisely capture change features in different regions of the image. …”
Get full text

A multi-scale rotated ship targets detection network for remote sensing images in complex scenarios by Siyu Li, Fei Yan, Yunqing Liu, Yuzhuo Shen, Lan Liu, Ke Wang

“…The model can gather information from any position in the sequence, extract contextual information of targets at different scales, and enhance global feature representation. …”
Get full text

Quantitative analysis of the nephron during human fetal kidney development by Daković-Bjelaković Marija Z., Vlajković Slobodan R., Čukuranović Rade E., Antić Svetlana, Bjelaković Goran B., Mitić Dejan

“…Glomeruli changed their size and shape, while the tubules changed their length and convolution. Renal cortex became wider and contained the more mature glomeruli and the more convoluted tubules. …”
Get full text

Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture by A. V. Kamenskiy, T. M. Akaeva, D. A. Grebenshchikova

“…In order to resolve this issue, adaptive filters with different sizes of multielement processing aperture are being developed to improve image clarity and preserve image details. …”
Get full text