Ultrawideband Non-Line-of-Sight Classification Using Transformer-Convolutional Neural Networks by Hae-Ji Hwang, Seon-Geun Jeong, Won-Joo Hwang

“…While recent deep learning methods, such as convolutional neural networks and long short-term memory models, have been applied to classify non-line-of-sight scenarios from raw channel impulse response data, they often struggle with capturing long-range dependencies, efficiently extracting spatial and temporal features, resulting in suboptimal classification performance. …”
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Real-Time Human Group Detection and Clustering in Crowded Environments Using Enhanced Multi-Object Tracking by Hyunmin Lee, Donggoo Kang, Hasil Park, Sangwoo Park, Dasol Jeong, Joonki Paik

“…Traditional trajectory-based methods often struggle with occlusions and overlapping behaviors, leading to inaccurate group identification. To address these limitations, we propose a novel algorithm that integrates an optimized YOLOv8 model with DeepSORT tracking, enhancing both detection accuracy and real time performance. …”
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A LithoScanner logging data processing method and application applicable to shale oil formation by Xuan Hu, Zhen Lin Wang, Jing Su, Wang Wang Yang, Xiao Xuan Chen, Peng Liu, Lei Zhao

“…Lithology identification is crucial for understanding the characteristics of reservoirs, optimizing development plans, and enhancing development efficiency. …”
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A comprehensive review-current development in spectroscopic and chromatographic techniques for natural product analysis by Abraham Dilnesa Gashaw, Mekonnen Abebayehu Desta, Estifanos Ele Yaya

“…Hyphenated analytical platforms are highlighted as valuable tools for the de novo identification, distribution, quantification, and authentication of constituents found in biogenic raw materials, natural medicines, and biological materials from plants, animals, humans, and model organisms. …”
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AI-Driven Ensemble Classifier for Jamming Attack Detection in VANETs to Enhance Security in Smart Cities by Walid El-Shafai, Ahmad Taher Azar, Saim Ahmed

“…These findings underscore the superiority of our proposed model over existing jamming detection models. The integration of this model into existing VANET security systems is anticipated to significantly enhance their capability to mitigate jamming attacks, thereby reinforcing the overall security and reliability of VANET communications. …”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

“…Compared to existing methods, our approach shows significant advantages in detection accuracy, localization precision, and model computational efficiency, achieving improved detection performance on the tomato leaf disease dataset.…”
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Transfer learning with XAI for robust malware and IoT network security by Ahmad Almadhor, Shtwai Alsubai, Natalia Kryvinska, Abdullah Al Hejaili, Belgacem Bouallegue, Mohamed Ayari, Sidra Abbas

“…We conducted extensive experiments showing improved accuracy and efficiency in cross-domain detection scenarios. Further, we demonstrate that transfer learning minimises training time and computational requirements compared to training separate models from scratch. …”
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Development and Investigation of Vision System for a Small-Sized Mobile Humanoid Robot in a Smart Environment by Amer Tahseen Abu-Jassar, Hani Attar, Ayman Amer, Vyacheslav Lyashenko, Vladyslav Yevsieiev, Ahmed Solyman

“…The decentralization of the servomotor control and the computer vision systems is investigated based on the hardware solution point of view, moreover, the required software level to achieve an efficient matched design is obtained. A computer vision system using the upgraded tiny-You Only Look Once (YOLO) network model is developed to allow recognizing and identifying objects and making decisions on interacting with them, which is recommended for crowd environment. …”
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Experimental Study on Long Short-term Memory Networks for Identifying P-wave Primary Phase by Tianzhe WANG, Wanji ZHANG, Shanbo QI, Guoming JIANG

“…Identifying primary phases of seismic waveforms is a routine task in seismic data processing. Owing to the low efficiency of manual identification and the influence of human subjective factors, many methods for the automatic identification of the primary phase have been developed in recent years. …”
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Anti-drift pose tracker (ADPT), a transformer-based network for robust animal pose estimation cross-species by Guoling Tang, Yaning Han, Xing Sun, Ruonan Zhang, Ming-Hu Han, Quanying Liu, Pengfei Wei

“…Extensive experiments across cross-species datasets—including proprietary mouse and monkey recordings and public Drosophila and macaque datasets—demonstrate that ADPT significantly reduces drift and surpasses existing models like DeepLabCut and SLEAP in accuracy. Moreover, ADPT achieved 93.16% identification accuracy for 10 unmarked mice and 90.36% accuracy for freely interacting unmarked mice, which can be further refined to 99.72%, enhancing both anti-drift performance and pose estimation accuracy in social interactions. …”
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Application of a nature-based solution adaptive management framework for improving coastal resiliency in a highly urbanized environment by Andrew McQueen, Burton Suedel, Sara Copp Franz, Tina Cardona, Molly McDermott, Sabrina Collins, Victor Magar, Jeffrey Herzog

“…With the simultaneous rise in coastal flooding risks projected by current climate models and the escalating demands placed on urban infrastructure by population expansion, there is an urgent need for resilient solutions to address these challenges. …”
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Multi-source 3D point clouds fusion for potential rock mass hazard evaluation in high-steep rock slopes by W. Yuan, C. Liu, C. Liu, T. Wang, B. Adriano, H. Bao, R. Shibasaki, S. Koshimura

“…The results demonstrate that the fusion of TLS-UAV multi-source data enhances spatial coverage and point cloud density by 19%, enabling comprehensive slope modeling and improving multi-angle structural characterization of target rock masses. …”
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MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images by Huinan Guo, Congying Sun, Jing Zhang, Wuxia Zhang, Nengshuang Zhang

“…The precise ability for object localization and identification enables remote sensing imagery to provide early warnings, mitigate risks, and offer strong support for decision-making processes. …”
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Meta Ag: An automatic agricultural contextual metadata collection app by Md. Samiul Basir, Yaguang Zhang, Dennis Buckmaster, Ankita Raturi, James V. Krogmeier

“…These results highlight its effectiveness as a deployable, efficient solution for agricultural metadata collection. …”
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A hybrid YOLO-UNet3D framework for automated protein particle annotation in Cryo-ET images by Ziyang Liu, Chunhong Yuan, Zixin Zhang, Xiang Zhou, Xiangyu Li, Zhen Tian, Yuting Pei, Zuowen Jiang, Zhikui Tian

“…Abstract Accurate localization and identification of protein complexes in cryo-electron tomography (cryo-ET) volumes are essential for understanding cellular functions and disease mechanisms. …”
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TE23D: A Dataset for Earthquake Damage Assessment and Evaluation by Can Ekkazan, M. Elif Karsligil

“…By offering a focused benchmark, this dataset enables an efficient identification of damaged areas by earthquakes. …”
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Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) by Montaser N.A. Ramadan, Mohammed A.H. Ali, Shin Yee Khoo, Layth Hamad, Mohammad Alkhedher

“…PIORS stands as the first-ever portable, AI-powered device tailored for rapid and accurate oil type identification, capable of delivering results within a mere five seconds. …”
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Etiology of Tendency Toward Using Cannabis: A Qualitative Study of the Lived Experiences of Teenager’s Consumers by Soodabeh Rostami, Atousa Kalantar Hormozi, Mohammad Asgari, Ezzatollah Kordmirza Nikoozadeh

“…The analysis of the participants’ experiences led to the identification of 136 primary codes, 30 sub-categories, 11 main categories, and 2 core categories. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Abstract Dementia rates are projected to increase significantly by 2050, posing considerable challenges for healthcare systems worldwide. Developing efficient diagnostic tools is critical, and machine learning (ML) algorithms have shown potential for improving the accuracy of cognitive impairment classification. …”
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Exploring drought risk scenarios for bioenergy systems for adaptation to climate change in the Upper Tocantins basin, Brazil by Jazmin Campos Zeballos, Vinicius Bof Bufon, Zita Sebesvari, Jakob Rhyner

“…The IPCC AR5 Risk Assessment Framework was employed to evaluate two global climate change models, two representative concentration pathways (RCPs), and three land use scenarios. …”
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