EVI‐SAM: Robust, Real‐Time, Tightly‐Coupled Event–Visual–Inertial State Estimation and 3D Dense Mapping by Weipeng Guan, Peiyu Chen, Huibin Zhao, Yu Wang, Peng Lu

“…A novel event‐based hybrid tracking framework is designed to estimate the pose, leveraging the robustness of feature matching and the precision of direct alignment. …”
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Enhancing dysarthria severity classification: efficient audio based deep learning models by Varsha J Varma, Aniruddha Jana, Arpan Kumar Samal, Aurobindo S, Rani Chinnappa Naidu, Somaya Al-Maadeed, Moutaz Saleh, Rajesh Kumar M, Prakash Ramachandran, Zachariah C Alex, Rajeev Khoodeeram

“…This paper presents a deep learning-based method based on TORGO dataset to overcome these challenges. Moreover, the problem statement focuses on the difficulty of exactly spotting dysarthria and assessing its degree of severity using traditional methods, which usually lack precision and efficiency. …”
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MEViT: Generalization of Deepfake Detection With Meta-Learning EfficientNet Vision Transformer by Van-Nhan Tran, Hoanh-Su Le, Piljoo Choi, Suk-Hwan Lee, Ki-Ryong Kwon

“…Furthermore, we introduce a pair-discrimination loss to push the feature representations of fake samples away from those of real samples, and a domain adjustment loss to reduce domain shifts across different manipulation methods. …”
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Token-Wise Asymmetric Contrastive Learning in Countering Unknown Attacks for Face Anti-Spoofing by Jimin Min, Yunho Jeon, Yonghyun Jeong, Youngjoon Yoo, Haneol Jang

“…The key idea to resolve the problem is to learn a feature space where live face features are densely distributed, whereas spoof face features are more dispersed. …”
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Detection of Leaf Miner Infestation in Chickpea Plants Using Hyperspectral Imaging in Morocco by Mohamed Arame, Issam Meftah Kadmiri, Francois Bourzeix, Yahya Zennayi, Rachid Boulamtat, Abdelghani Chehbouni

“…This study addresses the problem of early detection of leaf miner infestations in chickpea crops, a significant agricultural challenge. …”
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Fault Diagnosis of Magnetically Controlled On-Column Circuit Breaker Based on Small Sample Condition by He Tian, Chao Liang, Wenpeng Ma, Tianchang Zhang

“…Subsequently, to address the problem of real-world operational data being susceptible to noise, a Stacked Denoising Autoencoder (SDAE) is utilized as the discriminator in the ACGAN framework. …”
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ADWNet: An improved detector based on YOLOv8 for application in adverse weather for autonomous driving by Xinyun Feng, Tao Peng, Ningguo Qiao, Haitao Li, Qiang Chen, Rui Zhang, Tingting Duan, JinFeng Gong

“…To address the problem of information loss in fused features, Neck has been replaced with RepGDNeck. …”
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BFER-Net: Babies Facial Expression Recognition Model Using ResNet12 Enabled Few-Shot Embedding Adaptation and Convolutional Block Attention Modules by Sumiya Arafin, Adnan Ferdous Ashrafi, Md. Golam Rabiul Alam, Ashis Talukder

“…Here, we have deployed the feature extraction process. A Convolutional Block Attention Module (CBAM) was integrated into the Modified ResNet12 architecture. …”
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Anytime Optimal Trajectory Repairing for Autonomous Vehicles by Kailin Tong, Martin Steinberger, Martin Horn, Selim Solmaz, Daniel Watzenig

“…Our paper introduces a groundbreaking approach by formulating an optimal trajectory repairing problem and proposing an innovative and efficient framework for critical timing detection and trajectory repairing. …”
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YOLOv7-DWS: tea bud recognition and detection network in multi-density environment via improved YOLOv7 by Xiaoming Wang, Xiaoming Wang, Zhenlong Wu, Guannan Xiao, Guannan Xiao, Chongyang Han, Cheng Fang

“…The problem of simultaneous detection and classification of one-bud-one-leaf and one-bud-two-leaves of tea was solved. …”
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Optimization of Anesthetic Provision During Operations on the Foot by D. S. Yasnev, A. V. Zabusov, S. V. Larionov, P. A. Lyubashevsky, P. S. Zhbannikov

“…The important feature of a heavy trauma of the foot is infringement regional haemocirculation of development of a vascular spasm. …”
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Multi-scale extreme climate disaster prediction model integrated with ConvLSTM: taking rainstorm and flood disaster as an example by Lei He, Yunhao He, Yongqiang Xia, Yuxia Li, Bin Liu, Siqi Zhang, Cunjie Zhang

“…Firstly, four disaster indicators (population disaster index, housing disaster index, agricultural disaster index and economic disaster index) were introduced to reflect different losses, which could form a comprehensive disaster index to quantify the overall loss degree; Second, with raster data and VGGNet, a lightweight regression convolutional neural network model VGG-Light was proposed to solve these problem; Third, focused on impact of precipitation on disaster situations, the ConvLSTM module was used to capture the spatiotemporal characteristics of precipitation data, and then the TSVGG-Light model was presented for feature fusion. …”
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Learning Spectral–Spatial-Former Deep Prior for Hyperspectral Image Superresolution by Zeinab Dehghan, Jingxiang Yang, Abdolraheem Khader, Jian Fang, Liang Xiao

“…By implementing multiscale spatial-aware and multidepth channel-aware modules, we generate comprehensive deep spatial–spectral prior feature maps. The spatial branch focuses on using local–global prior features for HS image reconstruction, while the spectral branch emphasizes the most informative channels and their correlations. …”
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ST-AGRNN: A Spatio-Temporal Attention-Gated Recurrent Neural Network for Traffic State Forecasting by Jian Yang, Jinhong Li, Lu Wei, Lei Gao, Fuqi Mao

“…The localized temporal features are obtained by gated recurrent unit (GRU). …”
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Design of English Intelligent Simulated Paper Marking System by Lina Yang, Wei Liu

“…This paper also extracts word features, sentence features, and chapter structure features in essays to fit English composition scores. …”
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A Global-to-Local Spectral-Spatial Attention-Based Nonlinearity and Scaled Endmember Variability Parametric Learning Network for Unmixing by Yi Zhao, Bin Yang

“…Unfortunately, significant unmixing residuals often arise from the coupled nonlinear mixing effects and spectral variability (SV), bringing challenges for reliably solving the underlying optimization problems in practical applications. Although deep autoencoder (AE) architectures have shown advantages in learning latent unmixing features from hyperspectral data, their performance in capturing accurate spectral-spatial information and interpreting both nonlinearity and SV remains limited. …”
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PROBLEMATIC ISSUES OF COMBINED INTESTINAL INFECTIONS by V. V. Shkarin, O. A. Chubukova, A. S. Blagonravova, A. V. Sergeeva

“…The  article  presents the  possible combinations of intestinal   infections of  various   etiologies, some   pathogenetic, clinical  and  epidemiological features and  problems of epidemiological surveillance and  control  of  associated infections.  …”
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The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection by Xiaohui Li, Pan Fu, Kan Chen, Zhibin Lin, Erqing Zhang

“…In the acoustic emission (AE) detection for mechanical seal, the main difficulty is to reduce the background noise and to classify the dispersed features. To solve these problems and achieve higher detection rates, a new approach based on genetic particle filter with autoregression (AR-GPF) and hypersphere support vector machine (HSSVM) is presented. …”
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MAPM:PolSAR Image Classification with Masked Autoencoder Based on Position Prediction and Memory Tokens by Jianlong Wang, Yingying Li, Dou Quan, Beibei Hou, Zhensong Wang, Haifeng Sima, Junding Sun

“…First, MAPM designs a Masked Autoencoder (MAE) based on the transformer for pre-training, which can boost feature learning and improve classification results based on the number of labeled samples. …”
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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…To solve this problem, this paper proposes a hybrid method that combines multimodal data-aware attacks with Light Gradient Boosting Machine (LightGBM) and Support Vector Regression (SVR) agent models. …”
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