Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…Second, the G-Shuffle module is designed to significantly enhance feature extraction efficiency and interchannel information interaction, balancing computational complexity and detection accuracy. …”
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A Deep-Neural-Network-Based Surrogate Model for DC/AC Converter Topology Selection Using Multi-Domain Simulations by Gabriel Avila Saccol, Van-Hai Bui, Wencong Su

“…The selection of optimal DC/AC power converter topologies for specific applications is often a time-consuming and complex task, which can lead to suboptimal choices. …”
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Prototyping a graph-based approach for efficient vehicle tracking in a cluster controlled CCTV surveillance systems by Apurva NARAYAN, Charumathi PARIVALLAL, Olirva MAHESWARAN, Sarath CHANDRAN KALATHILPARAMBIL RAMACHANDRAN

“…Addressing the growing challenges of vehicle density and traffic complexity, the system employs state-of-the-art deep learning techniques for real-time vehicle detection, tracking, and route analysis. …”
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MSAN-Net: An End-to-End Multi-Scale Attention Network for Universal Industrial Defect Detection by Zelu Wang, Ming Luo, Xinghe Xie, Yue Sun, Xinyu Tian, Zhengxuan Chen, Junwei Xie, Qinquan Gao, Tong Tong, Yue Liu, Tao Tan

“…Traditional manual visual inspection or single-task deep learning models were often struggled to balance detection efficiency and accuracy in complex industrial scenarios. …”
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Novel transfer learning based acoustic feature engineering for scene fake audio detection by Ahmad Sami Al-Shamayleh, Hafsa Riasat, Ala Saleh Alluhaidan, Ali Raza, Sahar A. El-Rahman, Diaa Salama AbdElminaam

“…We have tuned hyperparameters of applied machine learning approaches, and cross-validation is applied to validate performance results. In addition, the complexity of the computation is measured. The proposed research aims to enhance the accuracy measure, and efficiency of identifying manipulated audio content, thereby contributing to the integrity and reliability of digital communications.…”
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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…The GSF-YOLOv8 not only significantly improves the efficiency and accuracy of fire detection but also provides a more reliable and accurate solution for real-time detection in similarly complex environments.…”
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Research on anomaly detection model for traffic time series data integrating multiple mechanisms by Peipei ZHANG, Jiaqi LIU

“…The results show that adding each module on the basis of LSTM significantly improves the model's prediction and anomaly detection ability; Compared with the general hybrid model Transformer-Bi-LSTM, the proposed model has stronger prediction ability and lower computational complexity. …”
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Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model by Yuan Liu, Yilong Liu, Xiaoyan Guo, Xi Ling, Qingyi Geng

“…On the AL10-DET dataset, SLF-YOLO achieves a mAP of 86.8%, striking an effective balance between detection accuracy and computational efficiency without increasing model complexity. …”
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Ambient Intelligence to Detect Misuse of Electricity Consumption Based on IoT Using Blockchain Technology by Soiful Hadi, Wahyul Amien Syafei, Adi Wibowo

“…Electricity abuse and energy inefficiencies are still open issues in smart grid systems, demanding high-performance anomaly detection mechanisms. In this paper, we propose an IoT-enabled electricity monitoring system that combines machine learning (LightGBM) and blockchain (Polygon network) for real-time anomaly detection, secure data storage, and transparent energy tracking. …”
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Enhancing land cover object classification in hyperspectral imagery through an efficient spectral-spatial feature learning approach. by Masud Ibn Afjal, Md Nazrul Islam Mondal, Md Al Mamun

“…Our approach leverages Seg-PCA for effective feature extraction and employs the minimum-redundancy maximum relevance (mRMR) criterion for feature selection. By combining the strengths of both 3D and 2D CNNs, our method efficiently extracts spectral-spatial features. …”
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DCEEMR: A Delay-Constrained Energy Efficient Multicast Routing Algorithm in Cognitive Radio Ad Hoc Networks by Xuna Miao, Miaolei Deng

“…We discuss the delay-constrained energy efficient multicast routing problem in cognitive radio ad hoc networks. …”
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An Improved Unmanned Aerial Vehicle Forest Fire Detection Model Based on YOLOv8 by Bensheng Yun, Xiaohan Xu, Jie Zeng, Zhenyu Lin, Jing He, Qiaoling Dai

“…Taking into account efficiency and cost-effectiveness, deep-learning-driven UAV remote sensing fire detection algorithms have emerged as a favored research trend and have seen extensive application. …”
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Fast Quality Detection of <i>Astragalus</i> Slices Using FA-SD-YOLO by Fan Zhao, Jiawei Zhang, Qiang Liu, Chen Liang, Song Zhang, Mingbao Li

“…Additionally, the integration of the SD module into the detection head optimizes parameter efficiency while improving detection performance. …”
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Target detection of helicopter electric power inspection based on the feature embedding convolution model. by Dakun Liu, Wei Zhou, Linzhen Zhou, Wen Guan

“…In addition, this study further optimizes the model with reinforcement learning technology, conducts a comparative analysis of different flight environments and facilities, and reveals the diversity and complexity of inspection objectives. The performance of the optimized model in fault detection is increased by more than 36%. …”
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Surface anomaly detection on island-based PV panels using edge neural networks by ZHANG Yinxian, ZHANG Zhanyao, ZHANG Xiya

“…Due to the poor accuracy and low efficiency of existing detection methods， the paper proposes a surface anomaly detection method for island-based PV panels using edge neural networks. …”
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A lightweight model for echo trace detection in echograms based on improved YOLOv8 by Jungang Ma, Jianfeng Tong, Minghua Xue, Junfan Yao

“…However, current detection models are too parameter-heavy to embed in echosounders and struggle with noisy, irregular, and dense echograms. …”
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Combination of Principal Component Analysis and Time-Frequency Representation for P-Wave Arrival Detection by Jacek Wodecki, Justyna Hebda-Sobkowicz, Adam Mirek, Radosław Zimroz, Agnieszka Wyłomańska

“…Due to the significant difference between the spectra of recorded seismic wave and pure noise which precedes the event, time-frequency representation allows for better accuracy of signal change detection. However, with an additional domain, the complexity rises. …”
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Leveraging Swarm Intelligence for Invariant Rule Generation and Anomaly Detection in Industrial Control Systems by Yunkai Song, Huihui Huang, Hongmin Wang, Qiang Wei

“…Conventional anomaly detection techniques often lack the ability to provide clear explanations for their detection, and their inherent complexity can impede practical implementation in the resource-constrained environments typical of ICSs. …”
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Hybrid Wavelet-Attention Model for Detecting Changes in High-Resolution Remote Sensing Images by Lhuqita Fazry, MGS M. Luthfi Ramadhan, Alif Wicaksana Ramadhan, Muhammad Febrian Rachmadi, Aprinaldi Jasa Mantau, Lukito Edi Nugroho, Chi-Hung Chi, Wisnu Jatmiko

“…However, this causes information loss, resulting in a trade-off between the effectiveness and efficiency of the method. To solve the problem, we developed a new change detection method called WaveCD. …”
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Exploring genomic feature selection: A comparative analysis of GWAS and machine learning algorithms in a large‐scale soybean dataset by Hawlader A. Al‐Mamun, Monica F. Danilevicz, Jacob I. Marsh, Cedric Gondro, David Edwards

“…Feature selection is important in large genomic data as it helps in enhancing interpretability and computational efficiency. …”
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