Integrating Fine-Grained Classification and Motion Relation Analysis for Face Anti-Spoofing by Ziyang Cheng, Xiafen Zhang

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RP-DETR: end-to-end rice pests detection using a transformer by Jinsheng Wang, Tao Wang, Qin Xu, Lu Gao, Guosong Gu, Liangquan Jia, Chong Yao

“…To tackle this issue, multiple models utilizing computer vision and deep learning have been applied. Owing to its high efficiency, deep learning is now the favored approach for detecting plant pests. …”
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Modeling of the mass attenuation coefficients of X ray beams using deep neural networks (DNN) and NIST database by GUSTAVO BERNARDES DA SILVA, VIVIANE RODRIGUES BOTELHO, Carla Diniz Lopes Becker, Cassiana Viccari, Thatiane A. Pianoschi

“…The best model of the manual approach received the following results: 0.19 and 0.08 for the loss function and MSE error metric, respectively. The absolute percentage error (MAE) of the difference in the results between the two models was: 0.065 and 0.044 for the Loss and MSE metrics. …”
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An Efficient Printing Defect Detection Based on YOLOv5-DCN-LSK by Jie Liu, Zelong Cai, Kuanfang He, Chengqiang Huang, Xianxin Lin, Zhenyong Liu, Zhicong Li, Minsheng Chen

“…Secondly, we incorporate the Large Selective Kernel (LSK) and RepConv modules into the feature fusion network, while also integrating a loss function that combines Normalized Gaussian Wasserstein Distance (NWD) with Efficient IoU (EIoU) to enhance the model’s focus on small targets. …”
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Lifetime Prediction Analysis of Proton Exchange Membrane Fuel Cells Based on Empirical Mode Decomposition—Temporal Convolutional Network by Chao Zheng, Changqing Du, Jiaming Zhang, Yiming Zhang, Jun Shen, Jiaxin Huang

“…Recent studies suggest deep learning approaches hold promise for this task. This study proposes a novel EMD-TCN-GN algorithm, which, for the first time, integrates empirical mode decomposition (EMD), temporal convolutional network (TCN), and group normalization (GN) by using EMD to adaptively decompose non-stationary signals (such as voltage fluctuations), the dilated convolution of TCN to capture long-term dependencies, and combining GN to group-calibrate intrinsic mode function (IMF) features to solve the problems of modal aliasing and training instability. …”
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EDRMM: enhancing drug recommendation via multi-granularity and multi-attribute representation by Feiyan Liu, Wenhao Wang, Jiawei Zheng, Yibo Xie, Xiaoli Wang, Dongxiang Zhang

“…We also design an adaptive global Drug–Drug Interaction (DDI) risk regularization term for the DDI loss function to better balance accuracy and safety during training. …”
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MSOAR-YOLOv10: Multi-Scale Occluded Apple Detection for Enhanced Harvest Robotics by Heng Fu, Zhengwei Guo, Qingchun Feng, Feng Xie, Yijing Zuo, Tao Li

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Multiscale guided attention network for optic disc segmentation of retinal images by A Z M Ehtesham Chowdhury, Andrew Mehnert, Graham Mann, William H. Morgan, Ferdous Sohel

“…This paper presents a deep machine-learning method for semantically segmenting OD from retinal images. …”
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Typology of media use and its associations with parent and child factors among elementary school children: a latent profile analysis by Yangmi Lim

“…In addition, higher levels of mothers’ permissive parenting styles were associated with an increased likelihood of belonging to the Games & entertainment-oriented/longest-use time profile rather than the Learning-oriented/shortest-use time profile. Overall, the members of the Games & entertainment-oriented/longest-use time profile exhibited the highest levels of problematic media use, executive function difficulties (planning–organizing, behavioral control, and attention–concentration difficulties), and externalizing and internalizing problems. …”
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Semi-Supervised Attribute Selection Algorithms for Partially Labeled Multiset-Valued Data by Yuanzi He, Jiali He, Haotian Liu, Zhaowen Li

“…In machine learning, when the labeled portion of data needs to be processed, a semi-supervised learning algorithm is used. …”
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ClioMD: An artificial intelligence model for ciliopathies by Ergören Mahmut Çerkez, Senturk Niyazi, Ali Manal Salah B., Özcelik İlkem Özce, Erol Kübra Damla, Temel Sehime Gulsun, Dundar Munis

“…Cilia are highly specialized cellular organelles that serve multiple functions in human development and health. Their central importance in the body is demonstrated by the emergence of various developmental disorders resulting from defects in cilia structure and function caused by different inherited mutations in more than 150 different genes. …”
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Generalization Enhancement Strategies to Enable Cross-Year Cropland Mapping with Convolutional Neural Networks Trained Using Historical Samples by Sam Khallaghi, Rahebeh Abedi, Hanan Abou Ali, Hamed Alemohammad, Mary Dziedzorm Asipunu, Ismail Alatise, Nguyen Ha, Boka Luo, Cat Mai, Lei Song, Amos Olertey Wussah, Sitian Xiong, Yao-Ting Yao, Qi Zhang, Lyndon D. Estes

“…Mapping agricultural fields using high-resolution satellite imagery and deep learning (DL) models has advanced significantly, even in regions with small, irregularly shaped fields. …”
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Vowel classification with combining pitch detection and one‐dimensional convolutional neural network based classifier for gender identification by Chia‐Hung Lin, Hsiang‐Yueh Lai, Ping‐Tzan Huang, Pi‐Yun Chen, Chien‐Ming Li

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osl-dynamics, a toolbox for modeling fast dynamic brain activity by Chetan Gohil, Rukuang Huang, Evan Roberts, Mats WJ van Es, Andrew J Quinn, Diego Vidaurre, Mark W Woolrich

“…At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. …”
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Computer task performance by subjects with Duchenne muscular dystrophy by Malheiros SR, Silva TD, Favero FM, Abreu LC, Fregni F, Ribeiro DC, de Mello Monteiro CB

“…Second, we examined correlations between the ability of subjects with DMD to learn the computational task and their motor functionality, age, and initial task performance.Method: The study included 84 individuals (42 with DMD, mean age of 18±5.5 years, and 42 age-matched controls). …”
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Multi-Modal Sensing for Propulsion Estimation in People Post-Stroke Across Speeds by Krithika Swaminathan, Dabin K. Choe, Daekyum Kim, Flore Barde, Teresa C. Baker, Nicholas C. Wendel, Andrew Chin, Gregoire Bergamo, Christopher J. Siviy, Christina Lee, Louis N. Awad, Terry D. Ellis, Conor J. Walsh

“…Rehabilitation literature indicates the need for such therapy to continue beyond the clinic in order to maintain motor function and support recovery. However, implementing community-based rehabilitation requires the ability to monitor gait in the real-world with clinically relevant accuracies. …”
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Constructing High-Quality Livable Cities: A Comprehensive Evaluation of Urban Street Livability Using an Approach Based on Human Needs Theory, Street View Images, and Deep Learning by Minzhi Li, Zhongxiu Fan

“…However, existing research primarily focuses on optimizing physical functions, neglecting the dynamic hierarchical nature and emotional experiences of residents’ needs. …”
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Machine learning using genotype and gene-expression data identifies alterations of genes involved in infection susceptibility, antigen presentation and cytokine signalling as key c... by Nicholas Pudjihartono, Daniel Ho, Justin Martin O’Sullivan

“…Background Previous genome-wide association studies (GWAS) have identified numerous genetic loci associated with juvenile idiopathic arthritis (JIA). However, the functional impact of these variants—particularly on tissue-specific gene expression—and which regulatory interactions make the greatest relative contribution to JIA risk remain unclear. …”
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Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model by Chuansheng Zhang, Minglai Yang

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Development of a machine learning-based risk assessment model for loneliness among elderly Chinese: a cross-sectional study based on Chinese longitudinal healthy longevity survey by Youbei Lin, Chuang Li, Xiuli Wang, Hongyu Li

“…The study examined the relationships between loneliness and factors such as functional limitations, living conditions, environmental influences, age-related health issues, and health behaviors. …”
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