Digital security risk identification and model construction of smart city based on deep learning by Zhilei Zhao

“…In order to deal with these problems, this paper designs a flexible three-layer architecture framework, and introduces a new intrusion detection feature selection method that combines flock optimization (CSO) and genetic algorithm (GA) to reduce the complexity of feature selection and enhance the detection and processing power of security vulnerabilities through deep neural networks (DNN). …”
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A nnU-Net-based automatic segmentation of FCD type II lesions in 3D FLAIR MRI images by Shubham Joshi, Millie Pant, Millie Pant, Arnav Malhotra, Kusum Deep, Vaclav Snasel

“…Manual detection is slow and challenging because the MRI features are subtle. Deep learning, especially convolutional neural networks, has shown great potential in automating image classification and segmentation by learning and extracting features. …”
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Drug target affinity prediction based on multi-scale gated power graph and multi-head linear attention mechanism. by Shuo Hu, Jing Hu, Xiaolong Zhang, Shuting Jin, Xin Xu

“…In order to accurately extract drug target features, we provide a gated skip-connection approach in multiscale graph neural networks, which is used to fuse multiscale features to produce a rich representation of feature information. …”
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Deep Learning Based DDoS Attack Detection by Xu Ziyi

“…On the CICDDoS2019 dataset, which included several DDoS attack versions, the suggested model was trained and evaluated. The hybrid CNN-LSTM has extraction capabilities regarding both the spatial and temporal features of network traffic data, showing highly efficient performance. …”
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Vers une conception centrée sur l’utilité by Emilie Loup-Escande

“…In this sense, it is a methodological tool which aims to guide VR engineers to design products focused not only on the features, but also on the needs and expectations of end users. …”
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IoT‐Based Elderly Health Monitoring System Using Firebase Cloud Computing by Adhan Efendi, Muhammad Imam Ammarullah, Indra Griha Tofik Isa, Meli Puspita Sari, Jasmine Nurul Izza, Yohanes Sinung Nugroho, Hamid Nasrullah, Denny Alfian

“…A comparative experiment is conducted to define the optimal supervised machine learning model to be deployed into the system by analysing evaluation metrics. Meanwhile, the user satisfaction aspect evaluated by the terms of usability, comfort, security, and effectiveness. …”
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A Deep Learning Method for Human Sleeping Pose Estimation with Millimeter Wave Radar by Zisheng Li, Ken Chen, Yaoqin Xie

“…To capture both frequency features and sequential features, we introduce ResTCN, an effective architecture combining Residual blocks and Temporal Convolution Network (TCN) to recognize different sleeping postures, from augmented statistical motion features of the radar time series. …”
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Multi-omics integrated analysis reveals the molecular mechanism of tail fat deposition differences in sheep with different tail types by Wannian Wang, Zhixv Pang, Siying Zhang, Pengkun Yang, Yangyang Pan, Liying Qiao, Kaijie Yang, Jianhua Liu, Ruizhen Wang, Wenzhong Liu

“…Abstract Background The accumulation of tail fat in sheep is a manifestation of adaptive evolution to the environment. Sheep with different tail types show significant differences in physiological functions and tail fat deposition. …”
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Fine-Grained Land Use Remote Sensing Mapping in Karst Mountain Areas Using Deep Learning with Geographical Zoning and Stratified Object Extraction by Bo Li, Zhongfa Zhou, Tianjun Wu, Jiancheng Luo

“…The former divides the complex mountain areas into manageable subregions to provide computational units and introduces a priori data for providing constraint boundaries, while the latter implements a processing mechanism with a deep learning (DL) of hierarchical semantic boundary-guided network (HBGNet) for different geographic objects of building, water, cropland, orchard, forest-grassland, and other land use features. …”
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AI-Powered Spectral Imaging for Virtual Pathology Staining by Adam Soker, Maya Almagor, Sabine Mai, Yuval Garini

“…Unstained human biopsy samples are scanned, and a Pix2Pix-based neural network generates realistic H&E-equivalent images. …”
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Target Tracking Algorithm Based on Adaptive Scale Detection Learning by Dawei Yang

“…The improvement point of this paper is to change the traditional kernel correlation filtering algorithm to detect and track at the same time and to combine deep learning with traditional kernel correlation filtering tracking to apply in the process of target tracking; the addition of deep learning network not only can learn more accurate feature representation but also can more effectively cope with the low resolution of video sequences, so that the algorithm in the case of scale mutation achieves more accurate target tracking in the case of scale mutation. …”
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A Multi-Branch Attention Fusion Method for Semantic Segmentation of Remote Sensing Images by Kaibo Li, Zhenping Qiang, Hong Lin, Xiaorui Wang

“…To address these challenges in remote sensing image semantic segmentation, we propose a highly generalizable multi-branch attention fusion method based on shallow and deep features. This approach applies pixel-wise, spatial, and channel attention mechanisms to feature maps fused with shallow and deep features, thereby enhancing the network’s semantic information extraction capability. …”
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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

“…Employing the Gamma test, among 31 features, 5 features (Luminance and Hue corresponding to YIQ color space, Autocorrelation, Contrast, and Correlation) were selected. …”
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Investigating a three-dimensional convolution recognition model for acoustic emission signal analysis during uniaxial compression failure of coal by Tao Wang, Zishuo Liu, Liyuan Liu

“…It effectively discerns diverse acoustic emission features through group convolution and evaluates their significance using the SE module. …”
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A Predictive Approach for Enhancing Accuracy in Remote Robotic Surgery Using Informer Model by Muhammad Hanif Lashari, Shakil Ahmed, Wafa Batayneh, Ashfaq Khokhar

“…The method is evaluated using the JIGSAWS dataset, achieving a prediction accuracy of over 90% under various network scenarios. …”
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Cutaneous non-volar melanoma dermoscopy and histopathology correlation: a systematic review protocol by Giuseppe Argenziano, Rita Bouceiro Mendes, Martinha Henrique, Pedro Augusto-Simões

“…Outcomes of interest include the association of at least one of the melanoma dermoscopy features (irregular pigmentation, blue-white veil, atypical network, multicomponent pattern, atypical dots and/or globules, regression, peripheral tan structureless area, negative network, shiny white structures, atypical vessels and streaks/pseudopods), with melanoma Breslow index or other histopathology characteristics (melanoma subtype, mitotic index and presence of ulceration). …”
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Epidemiological characterization of chronic myeloid leukaemia patients at an oncologic centre: A retrospective observational study by Ana Maria Meireles, Rita Calisto, Maria José Bento, Pedro Martinho Gouveia, Susana Bizarro, Manuel Teixeira, Cláudia Moreira, Ana Espírito Santo, Mário Mariz

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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…The Squeeze-and-Excitation Network (SENet) further boosts spatial feature extraction by dynamically adjusting the importance of different feature channels. …”
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Microgrid system for electric vehicle charging stations integrated with renewable energy sources using a hybrid DOA–SBNN approach by Kommoju Naga Durga Veera Sai Eswar, M. Arun Noyal Doss, Mohammad Shorfuzzaman, Ali Elrashidi

“…An evaluation in MATLAB compares DOA–SBNN with existing approaches, demonstrating its effectiveness in enhancing EV charging performance. …”
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A Deep Learning-Based Solution to the Class Imbalance Problem in High-Resolution Land Cover Classification by Pengdi Chen, Yong Liu, Yuanrui Ren, Baoan Zhang, Yuan Zhao

“…To address this issue, we propose the high-resolution U-shaped mamba network (HRUMamba), which integrates multiple innovations to enhance segmentation performance under imbalanced conditions. …”
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