Integration of YOLOv8 Small and MobileNet V3 Large for Efficient Bird Detection and Classification on Mobile Devices by Axel Frederick Félix-Jiménez, Vania Stephany Sánchez-Lee, Héctor Alejandro Acuña-Cid, Isaul Ibarra-Belmonte, Efraín Arredondo-Morales, Eduardo Ahumada-Tello

“…The evaluation metrics included precision, recall, and computational efficiency. Results: The findings demonstrate that both models achieve high accuracy in species identification. …”
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Molecular property prediction using pretrained-BERT and Bayesian active learning: a data-efficient approach to drug design by Muhammad Arslan Masood, Samuel Kaski, Tianyu Cui

“…This work establishes that combining pretrained molecular representations with active learning significantly improves both model performance and acquisition efficiency in drug discovery, providing a scalable framework for compound prioritization. …”
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Public health perspectives on green efficiency through smart cities, artificial intelligence for healthcare and low carbon building materials by Jingjing Sun, Xin Guan, Siqi Yuan, Yalin Guo, Yepei Tan, Yajuan Gao

“…The application of CNN models in the construction industry showcases a promising pathway to enhance material selection efficiency and foster sustainable practices. …”
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Leveraging artificial intelligence for diagnosis of children autism through facial expressions by Mahmood A. Mahmood, Leila Jamel, Nazik Alturki, Medhat A. Tawfeek

“…The authors assess the detection of autism-related learning difficulties in children by evaluating deep learning models that use transfer learning methods along with fine-tuning methods. …”
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A Channel Attention-Based Denoising Autoencoder U-Net and Classifier (UNA-DAEC) for Signal Identification Under Challenging SNR Conditions by Ife Olalekan Ebo, Idowu Ajayi, Lina Mroueh, Youmni Ziade, Sylvain Azarian

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Efficient and Non-Invasive Grading of Chinese Mitten Crab Based on Fatness Estimated by Combing Machine Vision and Deep Learning by Jiangtao Li, Hongbao Ye, Chengquan Zhou, Xiaolian Yang, Zhuo Li, Qiquan Wei, Chen Li, Dawei Sun

“…Here, we employed computer vision techniques combined with deep learning modeling to efficiently quantify key physiological traits, such as sex identification, carapace dimensions (length and width), and fatness assessment for quality classification. …”
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Individual Identification of Holstein Cows from Top-View RGB and Depth Images Based on Improved PointNet++ and ConvNeXt by Kaixuan Zhao, Jinjin Wang, Yinan Chen, Junrui Sun, Ruihong Zhang

“…Finally, body pattern image classification based on the improved ConvNeXt network model was performed for individual cow identification. …”
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Preliminary Development of Global–Local Balanced Vision Transformer Deep Learning with DNA Barcoding for Automated Identification and Validation of Forensic Sarcosaphagous Flies by Yixin Ma, Lin Niu, Bo Wang, Dianxin Li, Yanzhu Gao, Shan Ha, Boqing Fan, Yixin Xiong, Bin Cong, Jianhua Chen, Jianqiang Deng

“…In our previous study, we developed a GLB-ViT (Global–Local Balanced Vision Transformer)-based deep learning model for fly species identification, which demonstrated improved identification capabilities. …”
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GM-VGG-Net: A Gray Matter-Based Deep Learning Network for Autism Classification by Ebenezer Daniel, Anjalie Gulati, Shraya Saxena, Deniz Akay Urgun, Biraj Bista

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Extended Kalman filter on sparse identification of nonlinear systems: application to the SoC estimation of a phase change material-based energy storage by Mustapha Habib, Youssef Elomari, Felix Hochwallner, Adam Buruzs, Tilman Barz, Qian Wang

“…Since SoC is not a direct measurement, there is a need for highly accurate prediction models. In this article, we propose solving this challenge by employing sparse identification of nonlinear dynamics (SINDy) to unlock the nonlinear dynamic complexity of PCM-TES. …”
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Real-time identification of collapsed buildings triggered by natural disasters using a modified object-detection network with quasi-panchromatic images by Jiayi Ge, Qiao Wang, Hong Tang

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FETAL HEALTH RISK STATUS IDENTIFICATION SYSTEM BASED ON CARDIOTOCOGRAPHY DATA USING EXTREME GRADIENT BOOSTING WITH ISOLATION FOREST AS OUTLIER DETECTION by Firda Yunita Sari, Dian Candra Rini Novitasari, Abdulloh Hamid, Dina Zatusiva Haq

“…Premature birth and birth defects contribute significantly to infant mortality, highlighting the need for early identification of fetal health risks. This study uses XGBoost for fetal health classification, integrating IForest for outlier detection to improve model performance. …”
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Optimization of Soft Actuator Control in a Continuum Robot by Oleksandr Sokolov, Serhii Sokolov, Angelina Iakovets, Miroslav Malaga

“…The proposed method circumvents traditional curvature and length-based modeling by directly identifying the quasi-static input–output relationship between actuator pressures and the 6-DoF end-effector pose. …”
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Electrical model of the 90 nm MOSFET by A. M. Borovik, V. T. Khanko, V. R. Stempitsky

“…The proposed approach efficiency to identification, extraction and optimization of parameters of semiconductor devices electrical models is demonstrated by examples of BSIM4 and HiSIM2 models SPICE parameters extraction for standard design MOS transistors manufactured using the technology providing minimum channel length of 90 nm.…”
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Identification of Bacterial Oligopeptidase B Inhibitors from Microbial Natural Products: Molecular Insights, Docking Studies, MD Simulations, and ADMET Predictions by Malik Suliman Mohamed, Tilal Elsaman, Magdi Awadalla Mohamed, Eyman Mohamed Eltayib, Abualgasim Elgaili Abdalla, Mona Timan Idriss

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SSD-YOLO: a lightweight network for rice leaf disease detection by Canlin Pan, Shen Wang, Shen Wang, Yahui Wang, Chaoyang Liu

“…Results indicate that SSD-YOLO achieves average detection accuracies of 87.52%, 99.48%, and 98.99% for rice brown spot, rice blast, and bacterial blight respectively—improving upon original YOLOv8 by 11.11%, 1.73%, and 3.81%. The model remains compact at only 6MB while showing significant enhancements in both detection accuracy and speed, providing robust support for timely identification of rice diseases.…”
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Image Classification of Chicken Breed and Gender Using Deep Learning by Liuchao Zhu, Zixin Chen, Hanwen Zhang, Yanju Shan, Gaige Ji, Huanliang Xu, Jingting Shu, Junxian Huang

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Robustness evaluation of bus-subway composite network considering accessibility by Yi Cao, Xiangzun Bu, Jialong Zhang

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A Smart Semi‐Implantable Device Integrating Microchannel‐Enhanced Sampling and Multiplex Biochemical Testing for Deep Wound Monitoring and Pathogen Identification by Qilin Li, Chunyu Wei, Luming Xu, Jiao Zhang, Yuyu Li, Xiaohuan Lu, Rengui Xu, Honglian Guo, Peng Cao, Chenke Ouyang, Jiarong Xu, Wei Chen, Zheng Wang, Lin Wang

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Identification of risk factors associated with prolonged hospital stay following primary knee replacement surgery: a retrospective, longitudinal observational study by Martin Pitt, Andrew Judge, Tim Jones, Rebecca Wilson, Chris Penfold, Andrew Elliott, Ruta Margelyte, Ashley Blom, Maria Theresa Redaniel, Alison Harper, Emily Eyles, Tim Keen

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