The Cultural Value Validity of Digital Media Art Based on Deep Learning Network Model by Yuan Ruan

“…The enhancement of features and the suppression of irrelevant features realize the evaluation of artistic and cultural value. …”
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Integration of Nuclear, Clinical, and Genetic Features for Lung Cancer Subtype Classification and Survival Prediction Based on Machine- and Deep-Learning Models by Bin Xie, Mingda Mo, Haidong Cui, Yijie Dong, Hongping Yin, Zhe Lu

“…An influencing factor system was optimized based on the nuclear, clinical, and genetic features. Four machine-learning models—light gradient boosting machine (LightGBM), extreme gradient boosting (XGBoost), random forest (RF), and adaptive boosting (AdaBoost)—and three deep-learning models—multilayer perceptron (MLP), TabNet, and convolutional neural network (CNN)—were employed for subtype classification and OS prediction. …”
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EBDet: Ellipse Feature Encode and Balanced Decoupling Label Assignment for Arbitrary-Oriented Ship Detection in Optical Remote Sensing Images by Tianqi Zhao, Yunhan Sun, Jin Qian, Zheng Li, Yunxiao Gao, Zhikang Zhao, Yongcheng Wang

“…The dynamic decoupling label assignment (DDLA) strategy adaptively evaluates the sample space sensitivity, and mitigates the feature misalignment problem by decoupling positive samples in classification and regression. …”
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MRI Delta-Radiomics and Morphological Feature-Driven TabPFN Model for Preoperative Prediction of Lymphovascular Invasion in Invasive Breast Cancer by Yunhua Li BS, Jianfeng Yang MS, Pan Xiao MS, Haibo Liu BS, Yingjun Zhou BS, Xiuqi Yang MS, Gangwen Chen BS, Zhichao Zuo PhD

“…We have developed the Tabular Prior-data Fitted Network (TabPFN) algorithm, which synergistically combines clinical and MR morphological features with delta-radiomics, thereby substantially improving the performance of binary classification. …”
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PCES-YOLO: High-Precision PCB Detection via Pre-Convolution Receptive Field Enhancement and Geometry-Perception Feature Fusion by Heqi Yang, Junming Dong, Cancan Wang, Zhida Lian, Hui Chang

“…The ConvNeXtBlock with inverted bottleneck is introduced in the P4 layer, greatly improving small-target feature capture and semantic understanding. The second key innovation lies in the creation of the Efficient Feature Fusion and Aggregation Network (EFAN), which integrates a lightweight Spatial-Channel Decoupled Downsampling (SCDown) module and three innovative fusion pathways. …”
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FedBFGCN: A Graph Federated Learning Framework Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution by Hefei Wang, Ruichun Gu, Jingyu Wang, Xiaolin Zhang, Hui Wei

“…In addition, this framework also uses homomorphic encryption methods to enhance privacy protection and improve data security. The FedBFGCN was evaluated on standard reference network datasets (Cora, Citeseer, Polblogs), and experimental results showed that it has lower losses and higher performance in multiple aspects. …”
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Selection method for hybrid energy storage schemes for supply reliability improvement in distribution networks by Qian Li, Yuanbao Zhou, Yunxiao Zhang, Yuxin Fu

“…Abstract Hybrid energy storage (HES) plays a crucial role in enhancing the reliability of distribution networks. However, the distinct charging and discharging characteristics among different energy storage technologies pose challenges to the evaluation of HES technical features. …”
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Revealing job accessibility supported by public transit services using a graph convolutional network by Meihan Jin, Leiyu Liu, Yongxi Gong, Yu Liu, Christophe Claramunt

“…This research aims to uncover the contribution of public transit to job accessibility from a network modeling perspective. Job accessibility and public transit services are evaluated and synthesized into an origin-destination (OD) network derived from real commuting demand extracted from big data. …”
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DETECTION OF TEXT OBJECTS IN IMAGES OF REAL SCENES BASED ON CONVOLUTIONAL NEURAL NETWORK MODEL by N. N. Kuzmitsky

“…A model of text image detector based on a convolutional neural network architecture is presented, capable of synthesizing high-level features of images in the «black box» mode. …”
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“Optimizing sEMG Gesture Recognition with Stacked Autoencoder Neural Network for Bionic Hand” by Mr. Amol Pandurang Yadav, Dr. Sandip.R. Patil

“…This study presents a novel deep learning approach for surface electromyography (sEMG) gesture recognition using stacked autoencoder neural network (SAE)s. The method leverages hierarchical representation learning to extract meaningful features from raw sEMG signals, enhancing the precision and robustness of gesture classification. • Feature Extraction and Classification MODWT Decomposition: The sEMG signals were decomposed using the MODWT DECOMPOSITION(Maximal Overlap Discrete Wavelet Transform) to capture various frequency components. • Time Domain Parameters: A total of 28 features per subject were extracted from the time domain, including statistical and spectral features. • Classifier Evaluation: Initial evaluations involved Autoencoder and LDA (Linear Discriminant Analysis) classifiers, with Autoencoder achieving an average accuracy of 77.96 % ± 1.24, outperforming LDA's 65.36 % ± 1.09.Advanced Neural Network Approach: Stacked Autoencoder Neural Network: To address challenges in distinguishing similar gestures within grasp groups, a Stacked Autoencoder Neural Network was employed. …”
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Fourier Features and Machine Learning for Contour Profile Inspection in CNC Milling Parts: A Novel Intelligent Inspection Method (NIIM) by Manuel Meraz Méndez, Juan A. Ramírez Quintana, Elva Lilia Reynoso Jardón, Manuel Nandayapa, Osslan Osiris Vergara Villegas

“…A feed-forward neural network is employed to classify contour profiles based on quality properties. …”
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Studies on innovative energy startups’ topological roles and their correlation with success: based on temporal networks by Ying Wang, Qing Guan

“…The research examines the role attributes of startups and explores the temporal topological characteristics of the network. We propose a success evaluation model based on the features of successful startups to assess the potential of innovative energy startups.Results and DiscussionThe findings indicate that, despite their relatively small market share, innovative energy startups exert significant influence. …”
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Evolving Hybrid Deep Neural Network Models for End-to-End Inventory Ordering Decisions by Thais de Castro Moraes, Jiancheng Qin, Xue-Ming Yuan, Ek Peng Chew

“…This study investigates the performance drivers of hybrid CNN-LSTM architectures, coupled with an evolving algorithm for optimizing network configuration. <i>Results:</i> Empirical evaluation of real-world retail data demonstrates that our proposed models proficiently extract pertinent features and interpret sequential data characteristics, leading to more accurate and informed ordering decisions. …”
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DINCP: Dual Interaction Network for Digital Bathymetric Model Superresolution via Codebook Priors by Peikun Xiao, Jianping Wu, Shuo Ma, Haoming Jia, Yingjie Wang

“…To address this challenge, we propose the dual interaction network via codebook priors (DINCP). Instead of directly decoding low-resolution (LR) input to generate HR DBMs, we first pretrain a discrete codebook to capture high-quality terrain features. …”
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A Rotation Target Detection Network Based on Multi-Kernel Interaction and Hierarchical Expansion by Qi Wang, Guanghu Xu, Donglin Jing

“…To address this issue, this paper proposes a Rotation Target Detection Network based on Multi-kernel Interaction and Hierarchical Expansion (MIHE-Net) as a systematic solution. …”
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Securing Unmanned Aerial Vehicles Networks Using Pairing Free Aggregate Signcryption Scheme by Eman Abouelkheir

“…We verify the security features of the suggested scheme using a formal security evaluation method, the random oracle model, under confidentiality and unforgeability. …”
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qTrustNet Virtual Private Network (VPN): Enhancing Security in the Quantum Era by Hyoungsub Shim, Bongho Kang, Haejung Im, Duhyun Jeon, Seok-Min Kim

“…This innovative combination of WireGuard protocol, PQC algorithms, and PUF technology creates a VPN system with significantly improved security features. To validate its effectiveness, the performance of the proposed qTrustNet VPN was rigorously evaluated in a 10GbE NIC network environment. …”
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Ground-Based Remote Sensing Cloud Image Segmentation Using Convolution-MLP Network by Shuang Liu, Jiafeng Zhang, Zhong Zhang, Shuzhen Hu, Baihua Xiao

“…In this article, we propose a novel network named convolution-MLP network (Con-MLPNet) for ground-based remote sensing cloud image segmentation, which could effectively learn long-range dependencies via the combination of MLPs and the attention mechanism. …”
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Multimodal lightweight neural network for Alzheimer's disease diagnosis integrating neuroimaging and cognitive scores by Bhoomi Gupta, Ganesh Kanna Jegannathan, Mohammad Shabbir Alam, Kottala Sri Yogi, Janjhyam Venkata Naga Ramesh, Vemula Jasmine Sowmya, Isa Bayhan

“…The neurocognitive feature extraction module utilizes depthwise separable convolutions to process cognitive assessment data, which are then fused with multimodal imaging features. …”
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GTMALoc: prediction of miRNA subcellular localization based on graph transformer and multi-head attention mechanism by Xindi Huang, Jipu Jiang, Lifen Shi, Cheng Yan

“…The model integrates multi-source features which include the miRNA sequence similarity network, miRNA functional similarity network, miRNA–mRNA association network, miRNA–drug association network, and miRNA–disease association network. …”
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