Occupational mismatch in the labour market of selected EU countries by Alka Obadić, Viktor Viljevac

“…Regardless of occupation complexity, improvements and deteriorations in labour market conditions affect all groups uniformly. …”
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FoT: an efficient transformer framework for real-time small object detection in football videos by Wentao Zhang, Yaocong Yang

“…Abstract Football videos are playing an increasingly important role in event analysis and tactical evaluation within computer vision. Traditional object detection methods, relying on region proposals and anchor generation, struggle to balance real-time performance and accuracy in complex scenarios such as multi-view, motion blur, and small object recognition. …”
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SCoralDet: Efficient real-time underwater soft coral detection with YOLO by Zhaoxuan Lu, Lyuchao Liao, Xingang Xie, Hui Yuan

“…In recent years, climate change and marine pollution have significantly degraded coral reefs, highlighting the urgent need for automated coral detection to monitor marine ecosystems. However, underwater coral detection presents unique challenges, including low image contrast, complex coral structures, and dense coral growth, which limit the effectiveness of general object detection algorithms. …”
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Signal Detection in Intelligent Reflecting Surface-Assisted NOMA Network Using LSTM Model: A ML Approach by Haleema Sadia, Hafsa Iqbal, Syed Fawad Hussain, Nasir Saeed

“…In this article, we propose a machine learning (ML)-based approach to perform joint channel estimation and signal detection in an IRS-enabled uplink NOMA network under efficient mitigation of SIC error propagation. …”
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Ultra-lightweight tomatoes disease recognition method based on efficient attention mechanism in complex environment by Wenbin Sun, Zhilong Xu, Kang Xu, Lin Ru, Ranbing Yang, Rong Wang, Jiejie Xing

“…To address these issues, this study proposes a framework that integrates tomato leaf detection with leaf disease recognition. This framework includes a leaf detection model designed for diverse and complex environments, along with an ultra-lightweight model for recognizing tomato leaf diseases. …”
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MEViT: Generalization of Deepfake Detection With Meta-Learning EfficientNet Vision Transformer by Van-Nhan Tran, Hoanh-Su Le, Piljoo Choi, Suk-Hwan Lee, Ki-Ryong Kwon

“…In this study, we propose a model called MEViT, which integrates the EfficientNet Vision Transformer with a meta-learning framework to enhance generalization in deepfake detection. …”
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OE-YOLO: An EfficientNet-Based YOLO Network for Rice Panicle Detection by Hongqing Wu, Maoxue Guan, Jiannan Chen, Yue Pan, Jiayu Zheng, Zichen Jin, Hai Li, Suiyan Tan

“…Accurately detecting rice panicles in complex field environments remains challenging due to their small size, dense distribution, diverse growth directions, and easy confusion with the background. …”
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Benthos-DETR: a high-precision efficient network for benthic organisms detection by Weibo Rao, Gang Chen, Yifei Zhang, Jue Cang, Shusen Chen, Chenyang Wang

“…This study proposes Benthos-DETR, a benthic organisms detection network based on the RT-DETR network. In the backbone of Benthos-DETR network, the Efficient Block with the C2f module reinforces the shallow feature extraction operation in Benthos-DETR, enhancing the algorithm’s multi-scale perception. …”
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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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