BrYOLO-Mamba: A Approach to Efficient Tracheal Lesion Detection in Bronchoscopy by Yuejiao Cao, Jianzhong Zhang, Ruibing Zhuo, Jin Zhao, Yanting Dong, Tanzhen Liu, Hui Zhao

“…Although artificial intelligence has made significant progress in enhancing the accuracy and efficiency of medical image diagnosis, current systems still struggle to effectively capture long-range dependencies and fine-grained features in complex medical images. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…However, this task remains challenging due to variable high-altitude viewpoints, complex environmental interference, and limitations in algorithmic efficiency. …”
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Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis by Ben Gabrielson, Hanlu Yang, Trung Vu, Vince Calhoun, Tulay Adali

“…In this paper, we introduce an efficient subset-based form of the Tucker decomposition, by selecting coresets from the tensor modes such that the resulting core tensor can well-approximate the full tensor. …”
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Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms by Maryam Askari, Farid Khoshalhan, Hodjat Hamidi

“…Feature selection is crucial in machine learning and data mining, significantly impacting model performance and efficiency by reducing dimensionality, mitigating overfitting, and improving interpretability. …”
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ASAD: A Meta Learning-Based Auto-Selective Approach and Tool for Anomaly Detection by Nadia Rashid, Rashid Mehmood, Fahad Alqurashi, Saad Alqahtany, Juan M. Corchado

“…By automating the selection process, the method aims to reduce the reliance on trial-and-error methods, streamline the anomaly detection workflow, and lead to more robust, adaptable, and efficient anomaly detection systems. …”
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MDPruner: Meta-Learning Driven Dynamic Filter Pruning for Efficient Object Detection by Lingyun Zhou, Xiaoyong Liu

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Utilizing Detectron2 for accurate and efficient colon cancer detection in histopathological images by Luxi Chen, Jie Shen, Xinyu Li, Rongzhou Li, Xiaoyun Gao, Xiaoyun Gao, Xinyue Chen, Xinyue Chen, Xiaotian Pan, Xiaotian Pan, Xiaosheng Jin

“…The framework demonstrated high computational efficiency and robustness in handling the complexity of medical image data.DiscussionThese results highlight Detectron2’s effectiveness as a powerful tool for computer-aided diagnostics in colon cancer detection. …”
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DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model by Panpan Jiang, Xiaohua Yang, Yaping Wan, Tiejun Zeng, Mingxing Nie, Zhenghai Liu

“…To address these limitations, a lightweight and efficient anti-UAV detection model, DRBD-YOLOv8, is proposed in this paper. …”
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Cost-Efficient RSSI-Based Indoor Proximity Positioning, for Large/Complex Museum Exhibition Spaces by Panos I. Philippopoulos, Kostas N. Koutrakis, Efstathios D. Tsafaras, Evangelia G. Papadopoulou, Dimitrios Sigalas, Nikolaos D. Tselikas, Stefanos Ougiaroglou, Costas Vassilakis

“…However, it suffers from low accuracy (in NLOS traffic), noise, and multipath fading issues. In large complex spaces, such as museums, where heavy visitor traffic is expected to seriously impact the ability to maintain LOS, RSSI coupled with Bluetooth Low Energy (BLE) seems ideal in terms of market availability, cost-/energy-efficiency and scalability that affect competing technologies, provided it achieves adequate accuracy. …”
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SmartRipen: LSTM-GRU feature selection& XGBoost-CNN for fruit ripeness detection by Archana Ganesh Said, Bharti Joshi

“…A Bacterial Foraging Optimizer (BFO) built around variance maximization retains high-density as well as discriminative features during feature selection. A novel Convolutional XGBoost Network (CXGBN) combines CNN's completely connected layers with XGBoost classifications for enhanced efficiency. …”
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Federated Learning for Fall Detection With Multimodal Residual Fusion and Pareto-Optimized Client Selection by Bao-Quan Wang, Fan Yang, Yi Wang, Fan Zhao, Yun-Fei Han, Yu-Peng Ma

“…However, challenges such as multimodal data integration and joint analysis in Internet of Medical Things (IoMT) environments and data heterogeneity across sources hinder efficient and accurate fall detection. This paper proposes a Federated Learning-based framework with Multimodal Residual Fusion and Pareto-optimized Client Selection (FLPCS-MRF). …”
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YOLOv8n-CSD: A Lightweight Detection Method for Nectarines in Complex Environments by Guohai Zhang, Xiaohui Yang, Danyang Lv, Yuqian Zhao, Peng Liu

“…To improve the accuracy of nectarine fruit recognition in complex environments and to increase the efficiency of automatic orchard-picking robots, a lightweight nectarine detection method, YOLOv8n-CSD, is proposed in this study. …”
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MFA-net: Object detection for complex X-ray cargo and baggage security imagery. by Thanaporn Viriyasaranon, Seung-Hoon Chae, Jang-Hwan Choi

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SDES-YOLO: A high-precision and lightweight model for fall detection in complex environments by Xiangqian Huang, Xiaoming Li, Limengzi Yuan, Zhao Jiang, Hongwei Jin, Wanghao Wu, Ru Cai, Meilian Zheng, Hongpeng Bai

“…In the field of object detection, while YOLOv8 has recently made notable strides in detection accuracy and speed, it still faces challenges in detecting falls due to variations in lighting, occlusions, and complex human postures. …”
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Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set by Jinna Li, Yuan Li, Haibin Yu, Yanhong Xie, Cheng Zhang

“…A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. …”
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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

“…Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  …”
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Enhanced Anomaly Detection in IoT Networks Using Deep Autoencoders with Feature Selection Techniques by Hamza Rhachi, Younes Balboul, Anas Bouayad

“…Compared to some IoT-based anomaly detection models, the experimental results reveal that the suggested model is more efficient at enhancing the accuracy of detecting malicious data. …”
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Real-Time Power System Event Detection: A Novel Instance Selection Approach by Gabriel Intriago, Yu Zhang

“…This study presents a novel adaptation of the Hoeffding Adaptive Tree (HAT) classifier with an instance selection algorithm that detects and identifies cyber and non-cyber contingencies in real time to enhance the situational awareness of cyber-physical power systems (CPPS). …”
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A Parts Detection Network for Switch Machine Parts in Complex Rail Transit Scenarios by Jiu Yong, Jianwu Dang, Wenxuan Deng

“…This article proposes a complex scene rail transit switch machine parts detection network YOLO-SMPDNet (YOLO-based Switch Machine Parts Detecting Network). …”
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Deep Complex Gated Recurrent Networks-Based IoT Network Intrusion Detection Systems by Engy El-Shafeiy, Walaa M. Elsayed, Haitham Elwahsh, Maazen Alsabaan, Mohamed I. Ibrahem, Gamal Farouk Elhady

“…DCGR_IoT employs advanced techniques to enhance anomaly detection capabilities. Convolutional neural networks (CNN) are used for spatial feature extraction and superfluous data are filtered to improve computing efficiency. …”
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