Large-Scale Monitoring of Potatoes Late Blight Using Multi-Source Time-Series Data and Google Earth Engine by Zelong Chi, Hong Chen, Sheng Chang, Zhao-Liang Li, Lingling Ma, Tongle Hu, Kaipeng Xu, Zhenjie Zhao

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Ship behavior pattern recognition method based on hybrid graph neural networks by Lin Ma, Lin Ma, Hao Cao, Hao Cao, Guo-You Shi, Guo-You Shi

“…These models leverage standardized automatic identification system data to improve feature extraction and recognition accuracy.ResultsExperimental results demonstrate that the proposed models achieve over 98% accuracy in ship behavioral pattern recognition, with fast convergence and superior performance compared to conventional GNN-based methods.DiscussionThe models provide robust and efficient solutions for maritime traffic analysis, offering significant potential for real-world applications in ship monitoring, intelligent navigation, and maritime safety management.…”
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Detection of low-altitude infrared small targets for UAVs using a density-based artificial bee colony algorithm by Haixia Wang, Hailong Wang, Fen Han

“…Then, the DBABC algorithm is utilized to achieve efficient clustering and accurate identification of high-density areas. …”
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Exploring NAS for anomaly detection in superconducting cavities of particle accelerators by Lynda Boukela, Julien Branlard, Annika Eichler, Annika Eichler

“…It relies on the augmentation of a physical model-based anomaly detection approach with neural network models to distinguish the quenches from the other anomalies. …”
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Extensive comparison of protein sequence-based bioinformatics applications for predicting lysine succinylation sites: a comparative review by Hussam Alsharif

“…Hence, in this review, we summarize the challenges and restrictions in the development of succinylation prediction models and provide guidelines for more suitable and efficient computational methods.…”
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Implementation of green, lean and six sigma operations for sustainable manufacturing. A review by Khalid Nagadi

“…With ever increasing environmental concerns and global warming, green manufacturing has gained momentum to make the manufacturing processes sustainable and efficient. This review aims to analyse the models to integrate three different management systems that are green, six sigma and lean for the sustainability of various manufacturing processes. …”
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Soft Schemes for Earthquake-Geotechnical Dilemmas by Silvia García

“…As a consequence, a strong demand for advanced modeling and identification schemes arises. During the past years, soft computing techniques have been used for developing unconventional procedures to study earthquake geotechnical problems. …”
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A Feature-Fusion Technique-Based Alzheimer’s Disease Classification Using Magnetic Resonance Imaging by Abdul Rahaman Wahab Sait, Ramprasad Nagaraj

“…Conclusions: The findings highlight the potential of the proposed AD classification model in providing an interpretable and resource-efficient solution for healthcare centers. …”
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Kronecker convolutional feature pyramid for fault diagnosis in rolling bearings by Sadia Batool, Abbas Ali Abid, Muhammad Asif, Sagheer Abbas, Khan Muhammad Adnan, Asghar Ali Shah, Taher M. Ghazal

“…Furthermore, the proposed deep learning model for fault diagnosis is not able to provide efficient and reliable results and is vulnerable to degradation problems and lack of multi-scale feature extraction. …”
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TFSNet: A Time–Frequency Synergy Network Based on EEG Signals for Autism Spectrum Disorder Classification by Lijuan Shi, Lintao Ma, Jian Zhao, Zhejun Kuang, Sifan Wang, Han Yang, Haiyan Wang, Qiulei Han, Lei Sun

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Real‐time object detection for unmanned vehicles in Bangladesh: Dataset, implementation and evaluation by Muhammad Liakat Ali, Topu Biswas, Shahin Akter, Mohammed Farhan Jawad, Hadaate Ullah

“…A set of experimental evaluations demonstrate that the proposed method is effective and efficient in recognizing Bangladeshi vehicles. In all test road scenarios, the proposed computer vision system for road vehicle identification achieved 95.8% accuracy and 0.3 ms processing time for 200 epochs. …”
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Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination by Ashagrie Sharew Iyassu, Ashagrie Sharew Iyassu, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Zelalem G. Dessie, Zelalem G. Dessie, Temesgen T. Zewotir

“…The study was done with the aim of identifying appropriate confounder identification methods and examining confounders for the causal effect of a number of antenatal care visits on age-specific childhood vaccination.MethodsA family of generalized linear models with log link functions was used to model the covariate and the number of antenatal care association. …”
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Multi-kernel inception-enhanced vision transformer for plant leaf disease recognition by Sk Mahmudul Hassan, Kumar Sekhar Roy, Ruhul Amin Hazarika, Mehbub Alam, Mithun Mukherjee

“…Abstract The timely and precise identification of diseases in plants is essential for efficient disease control and safeguarding of crops. …”
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PlantNet: Scalable Convolutional Neural Network for Image-Based Plant Disease Detection by Sinha Anupa, Kumaraswamy Balasubramaniam

“…The architecture is composed of multiple convolutional and pooling layers, ensuring both depth and performance efficiency. To improve the model's generalizability in real-world conditions, data augmentation techniques—such as random rotations, shifts, and lighting adjustments—are applied to address variations in orientation, illumination, and background noise. …”
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A study and practice of end-to-end quality of service analysis scheme for 5G services based on autonomous network by Shicheng XU

“…Conducting end-to-end analysis of 5G service quality is the focus of operators to improve 5G user perception.Technical solutions such as rule engine, AI competency center, and intelligent scheduling were adopted to build a “fifth order closed-loop autonomous process” covering quality difference identification, quality difference definition, closed-loop management, effect analysis, and model iteration related to 5G service quality analysis.The process can make up for the shortage of the traditional end-to-end analysis of service quality that highly relies on solidified expert rules.According to this process, the end-to-end analysis scheme of 5G service quality of self-intelligent network was studied and practiced, achieving efficient autonomous collaboration and ensuring the perception of 5G service users.…”
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Feature scale and identifiability: how much information do point hydraulic measurements provide about heterogeneous head and conductivity fields? by S. K. Hansen, D. O'Malley, J. P. Hambleton

“…We find that significant feature identification becomes possible as feature scale exceeds 4 times the measurement spacing, and identification reliability subsequently improves in a power-law fashion with increasing feature scale.…”
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Optimal pseudorandom sequence selection for online c-VEP based BCI control applications. by Jonas L Isaksen, Ali Mohebbi, Sadasivan Puthusserypady

“…Correct/incorrect identification and time consumption were obtained for each identification. …”
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Towards Precise Papaya Ripeness Assessment: A Deep Learning Framework with Dynamic Detection Heads by Haohai You, Jing Fan, Dongyan Huang, Weilong Yan, Xiting Zhang, Zhenke Sun, Hongtao Liu, Jun Yuan

“…Papaya ripeness identification is a key task in orchard management. To achieve efficient deployment of this task on edge computing devices, this paper proposes a lightweight detection model, ABD-YOLO-ting, based on YOLOv8. …”
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Fine-grained detection and segmentation of civilian aircraft in satellite imagery using YOLOv8 by Ramesh Kumar Panneerselvam, Sarada Bandi, Sree Datta Siva Charan Doddapaneni

“…This paper presents that by developing an efficient YOLOv8-based model for aircraft detection, classification, and segmentation within the FAIR1M-2.0 dataset. …”
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Indoor Air Pollution Source Localization Based on Small-Sample Training Convolutional Neural Networks by Tiancheng Ye, Mengtao Han

“…By integrating computational fluid dynamics simulation data and deep learning techniques, a spatial pollution source identification model suitable for limited-sample conditions was constructed. …”
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