YOLOv8n-WSE-Pest: A Lightweight Deep Learning Model Based on YOLOv8n for Pest Identification in Tea Gardens by Hongxu Li, Wenxia Yuan, Yuxin Xia, Zejun Wang, Junjie He, Qiaomei Wang, Shihao Zhang, Limei Li, Fang Yang, Baijuan Wang

“…The addition of the Spatial and Channel Reconstruction Convolution structure in the Backbone layer reduces redundant spatial and channel features, thereby reducing the model’s complexity. The integration of the Efficient Multi-Scale Attention Module with Cross-Spatial Learning enables the model to have more flexible global attention. …”
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A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

“…There is an urgent need to investigate the critical technologies of intelligent picking robots for tea. The complexity of the model requires high hardware computing resources, which limits the deployment of the tea bud detection model in tea-picking robots. …”
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Integration of deep learning and railway big data for environmental risk prediction models and analysis of their limitations by Liuhui Quan, Minjie Wang, Lyu Baihang, Zhang Ziwen, Zhang Ziwen, Zhang Ziwen

“…The rapid evolution of railway systems, driven by digitization and the proliferation of Internet-of-Things (IoT) devices, has resulted in an unprecedented volume of diverse and complex data. This railway big data offers immense opportunities for advancing safety, efficiency, and sustainability in transportation but presents significant analytical challenges due to its heterogeneity, high-dimensionality, and temporal dependencies. …”
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Edge-Based Dynamic Spatiotemporal Data Fusion on Smart Buoys for Intelligent Surveillance of Inland Waterways by Ruolan Zhang, Chenhui Zhao, Yu Liang, Jingfeng Hu, Mingyang Pan

“…Additionally, a novel regional division and a Kalman filter-based method for AIS and video data fusion were proposed, effectively resolving the issues of data sparsity and coordinate transformation robustness under complex waterway conditions. This approach substantially advances the precision and efficiency of waterway monitoring systems, providing a robust theoretical and practical framework for the intelligent supervision of inland waterways.…”
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Towards an automatized and objective assessment of data from visual inspections of building envelopes by Jan Mandinec, Pär Johansson

“…These make the decisions upon what and when to renovate a complex and ambiguous problem. Selection of renovation measures related to building envelope are often far from optimal as decisions are usually made based on visual inspections. …”
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Multimodal malware classification using proposed ensemble deep neural network framework by Sadia Nazim, Muhammad Mansoor Alam, Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Su’ud

“…Deep learning (DL) aids in accurately classifying complex malware features. The cross-domain research in data fusion strives to integrate information from multiple sources to augment reliability and minimize errors in detecting sophisticated cyber threats. …”
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Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management by Tejasva Maurya, Saurabh Kumar, Mritunjay Rai, Abhishek Kumar Saxena, Neha Goel, Gunjan Gupta

“…To optimize performance, the model leverages the YOLOv8 deep learning framework, known for its speed and precision in object detection. By using transfer learning with pre‐trained YOLOv8 weights, the model improves accuracy and efficiency, particularly in low‐resource environments. …”
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The use and integration of airborne laser scanning and satellite time series data in precision forest management for plantations of fast-growing tree species by Gonzalo Gavilan-Acuna, Nicholas C. Coops, Piotr Tompalski, Dominik Roeser, Andrés Varhola

“…ALS-based Enhanced Forest Inventories provide spatially detailed forest metrics, while satellite time series and vegetation indices support continuous monitoring of growth and early detection of drought, fire, and pest stress. ALS individual tree detection models offer insights into competition, stand structure, and spatial variability, informing thinning and fertilization decisions by identifying trees under stress or with high growth potential. …”
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A dual fluorescence channel RAA-based CRISPR-Cas12a/Cas13a system for highly sensitive detection of Gyrovirus galga1 and Gyrovirus homsa1 by Dan Yu, Zhixun Xie, Yanfang Zhang, Zhiqin Xie, Qing Fan, Sisi Luo, Liji Xie, Meng Li, Tingting Zeng, Minxiu Zhang, Xiaofeng Li, You Wei, Aiqiong Wu, Lijun Wan

“…These findings demonstrate that our RAA-based CRISPR – Cas12a/Cas13a dual-channel detection system can detect two different subtypes of gyrovirus in a sample with good specificity and high sensitivity, improving the detection efficiency and providing a new technique for the study of viral infection dynamics.…”
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Advances in Online Grain Quality Assessment: Near-Infrared Spectroscopic Modeling and Transfer Strategies by CUI Chen-hao, FAN Chen

“…However, the high dimensionality, complexity of NIR spectral data, and variations among different instruments, environments, and samples pose challenges to modeling methods and model transfer. …”

Lightweight Deep Learning Model for Fire Classification in Tunnels by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…Tunnel fires pose a severe threat to human safety and infrastructure, necessitating the development of advanced and efficient fire detection systems. This paper presents a novel lightweight deep learning (DL) model specifically designed for real-time fire classification in tunnel environments. …”
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MCRS-YOLO: Multi-Aggregation Cross-Scale Feature Fusion Object Detector for Remote Sensing Images by Lu Liu, Jun Li

“…However, remote sensing images typically exhibit the following characteristics: significant variations in object scales, dense small targets, and complex backgrounds. To address these challenges, a novel object detection method named MCRS-YOLO is innovatively proposed. …”
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Edge–Region Collaborative Segmentation of Potato Leaf Disease Images Using Beluga Whale Optimization Algorithm with Danger Sensing Mechanism by Jin-Ling Bei, Ji-Quan Wang

“…Precise detection of potato diseases is critical for food security, yet traditional image segmentation methods struggle with challenges including uneven illumination, background noise, and the gradual color transitions of lesions under complex field conditions. …”
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Inverse Gravimetric Problem Solving via Prolate Ellipsoidal Parameterization and Particle Swarm Optimization by Ruben Escudero González, Zulima Fernández Muñiz, Antonio Bernardo Sánchez, Juan Luis Fernández Martínez

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Adaptive Policy-Oriented Cybersecurity: A Decentralized Framework Using Message Passing Algorithms for Dynamic Threat Mitigation by Spyridon Evangelatos, Eleni Veroni, Mariza Konidi, Sophia Karagiorgou, Georgia Dede, Anargyros Baklezos, Christos Nikolopoulos, Panagiotis Sarigiannidis, Sotirios K. Goudos

“…However, the growing complexity of distributed systems and the interdependencies between diverse security components present significant challenges in ensuring consistent and efficient policy enforcement. …”
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Electrochemical Microneedles for Real-Time Monitoring in Interstitial Fluid: Emerging Technologies and Future Directions by Suhyeon Cha, Min Yu Choi, Min Jung Kim, Sang Baek Sim, Izzati Haizan, Jin-Ha Choi

“…Conventional blood-based detection methods for biomarkers and analytes face significant limitations, including complex processing, variability in blood components, and the inability to provide continuous monitoring. …”
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Optimization of particle filter tracking algorithm based on weakly supervised attribute learning by Hui Zhang, Dawang Shen

“…Abstract This study proposes an optimization method for particle filter tracking algorithm to solve the issues of low recognition efficiency and poor tracking accuracy faced by existing target tracking algorithms in complex environments. …”
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CAFiKS: Communication-Aware Federated IDS With Knowledge Sharing for Secure IoT Connectivity by Ogobuchi Daniel Okey, Demostenes Zegarra Rodriguez, Frederico Gadelha Guimaraes, Joao Henrique Kleinschmidt

“…In this paper, we introduce CAFiKS (Communication-Aware Federated Intrusion Detection System with Knowledge Sharing), a novel FL method designed to address the challenges of data heterogeneity, model complexity, and convergence rates. …”
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A DNN-based 5G MIMO system adopting a mix of tactics by Md. Matiqul Islam, Md. Ashraful Islam, Md. Firoz Ahmed

“…However, current methods often struggle with issues related to complexity and efficiency. This paper addresses these challenges by developing a multiple input multiple output (MIMO) system that integrates deep neural network (DNN) demappers, low-density parity-check (LDPC) coding, and polar coding, creating a mix of tactics aimed at boosting performance in flat fading channel environments. …”
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On the Design of Super Constellations by Thrassos K. Oikonomou, Dimitrios Tyrovolas, Sotiris A. Tegos, Panagiotis D. Diamantoulakis, Panagiotis Sarigiannidis, George K. Karagiannidis

“…By utilizing the decision regions formulated by GPD-D, a tight closed-form approximation for the symbol error probability (SEP) of SAPSK constellations is derived, while a detection algorithm with <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(1)$ </tex-math></inline-formula> time complexity is developed to ensure fast and efficient SAPSK symbol detection. …”
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