Research on graph-based heterogeneous data integration method by HUANG Yuezhen, YANG Fen, TIAN Feng, ZHANG Chengye, LI Yuchan

“…The table names and field names were regarded as different types of entities in the graph. Then, input the constructed graph into the graph neural network, and the vector representation of each node in the graph was obtained through graph convolution. …”
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NeuroTIS+: An Improved Method for Translation Initiation Site Prediction in Full-Length mRNA Sequence via Primary Structural Information by Wenqiu Xiao, Chao Wei

“…Second, it neglects the heterogeneity of negative TISs originating from different reading frames, which exhibit distinct coding features in their vicinity. …”
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Towards Automatic Detection of Pneumothorax in Emergency Care with Deep Learning Using Multi-Source Chest X-ray Data by Santiago Ibañez Caturla, Juan de Dios Berná Mestre, Oscar Martinez Mozos

“…In particular, we use datasets which contain chest X-ray images corresponding to different conditions (including pneumothorax). A convolutional neural network (CNN) with an EfficientNet architecture is trained and optimized to identify radiographic signs of pneumothorax using those public datasets. …”
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Terrain and Atmosphere Classification Framework on Satellite Data Through Attentional Feature Fusion Network by Antoni Jaszcz, Dawid Połap

“…Atrous convolutional operators were also used in such an architecture as better context feature extractors. …”
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Geological Stratification Technology Based on Artificial Intelligence Algorithms and Its Application Effects by GAO Yuan, YAO Weihua, CAI Shaofeng, LI Liang, XUE Yuan, ZHAO Peipei, WANG Xiaoyang, WEI Wei

“…Moreover, there are significant differences in stratification among different geological researchers, and the stratification results are unstable. …”
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Time Series Forecasting Method Based on Multi-Scale Feature Fusion and Autoformer by Xiangkai Ma, Huaxiong Zhang

“…Based on multi-scale convolutional operations, a multi-scale feature fusion network is proposed, combined with date–time encoding to build the MD–Autoformer time series forecasting model, which enhances the model’s ability to capture information at different scales. …”
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Linear-nonlinear cascades capture synaptic dynamics. by Julian Rossbroich, Daniel Trotter, John Beninger, Katalin Tóth, Richard Naud

“…Short-term synaptic dynamics differ markedly across connections and strongly regulate how action potentials communicate information. …”
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Optimizing the automated recognition of individual animals to support population monitoring by Tijmen A. deLorm, Catharine Horswill, Daniella Rabaiotti, Robert M. Ewers, Rosemary J. Groom, Jessica Watermeyer, Rosie Woodroffe

“…To evaluate intraspecific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat coloration patterns. The process of selecting suitable images was automated using convolutional neural networks that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. …”
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A hierarchical reinforcement learning approach for energy‐aware service function chain dynamic deployment in IoT by Shuyi Wang, Haotong Cao, Longxiang Yang

“…The suggested method is tested in three typical complicated networks with different network parameters to show its suitability in different network scenarios.…”
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CAPTCHA Recognition Method Based on CNN with Focal Loss by Zhong Wang, Peibei Shi

“…The traditional CAPTCHA recognition method has poor recognition ability and robustness to different types of verification codes. For this reason, the paper proposes a CAPTCHA recognition method based on convolutional neural network with focal loss function. …”
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Semi-supervised gearbox fault diagnosis under variable working conditions based on masked contrastive learning by ZHANG Huiyun, ZUO Fangjun, LI Hang, YU Xi

“…Secondly, a dynamic convolutional neural network was employed to dynamically weight and aggregate the masked instances, enabling discriminative feature modeling of different masked instances. …”
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Automated liver segmentation from CT images using modified ResUNet by R.V. Manjunath, Yashaswini Gowda N, H.M. Manu

“…In this study we proposed an automatic system that utilizes convolutional layers to efficiently extract features while maintaining spatial information. …”
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Ultrasound Localization of Nitinol Wire of Sub-Wavelength Dimension by D. R. DeVries, L. J. Olafsen, J. S. Olafsen, H. H. Nguyen, K. E. Schubert, S. Dayawansa, J. H. Huang

“…<italic>Results:</italic> For the full range of diameters traversing the phantom, the wires were localized successfully via visual inspection of both regular and difference ultrasound images. Similarly, two convolutional neural networks were trained, and both achieved an accuracy of over 95&#x0025;. …”
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Method to generate cyber deception traffic based on adversarial sample by Yongjin HU, Yuanbo GUO, Jun MA, Han ZHANG, Xiuqing MAO

“…In order to prevent attacker traffic classification attacks,a method for generating deception traffic based on adversarial samples from the perspective of the defender was proposed.By adding perturbation to the normal network traffic,an adversarial sample of deception traffic was formed,so that an attacker could make a misclassification when implementing a traffic analysis attack based on a deep learning model,achieving deception effect by causing the attacker to consume time and energy.Several different methods for crafting perturbation were used to generate adversarial samples of deception traffic,and the LeNet-5 deep convolutional neural network was selected as a traffic classification model for attackers to deceive.The effectiveness of the proposed method is verified by experiments,which provides a new method for network traffic obfuscation and deception.…”
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Enhanced pedestrian trajectory prediction via overlapping field-of-view domains and integrated Kolmogorov-Arnold networks. by Hongxia Wang, Yang Liu, Zhenkai Nie

“…By rigorously dividing monocular and binocular overlapping visual regions and utilizing different influence factors, the model pedestrian interactions more realistically. …”
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Synergizing BRDF correction and deep learning for enhanced crop classification in GF-1 WFV imagery by Yuanwei Chen, Yang Li, Runze Li, Chongzheng Guo, Jilin Li

“…First, a BRDF correction method based on normalized difference vegetation index (NDVI) and anisotropy flat index (AFX) is developed to normalize radiometric discrepancies. …”
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Machine Learning Prediction of Storm‐Time High‐Latitude Ionospheric Irregularities From GNSS‐Derived ROTI Maps by Lei Liu, Y. Jade Morton, Yunxiang Liu

“…Abstract This study presents an image‐based convolutional long short‐term memory (convLSTM) machine learning algorithm to predict storm‐time ionospheric irregularities. …”
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KSC-Net: a biologically inspired spatio-temporal correlation network for video-based human action recognition by Hui Ma, Xuelian Ma

“…To address these limitations, we propose a biologically inspired two-branch convolutional network, termed Key-information Spatio-temporal Correlation Network (KSC-Net). …”
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Algorithm for Extraction of Reflection Waves in Single-Well Imaging Based on MC-ConvTasNet by Wanting Lin, Jiaqi Xu, Hengshan Hu

“…In the signal channels of the common-source gather, there exists a notable arrival time difference between direct waves and reflected waves. …”
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WDM C-band four channel demultiplexer using cascaded multimode interference on SiN strip waveguide structure by Malka Dror

“…Our design was optimized using AI-enhanced RSoft-CAD simulations that combined the Beam Propagation Method (BPM) and Finite-Difference Time-Domain (FDTD) techniques, integrated with convolutional neural network (CNN) machine learning algorithms. …”
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