Hedge Funds As a Alternative Investment Opportunities by Michał Falkowski

“…The paper deals with the current problem of the financial crisis and the effect it made worldwide for many institutional and private investors. …”
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Plug-and-Play Robust Aerial Object Detection Under Hazy Conditions by Wei Wu, Hao Chang, Zhiwen Chen, Zhu Li

“…Moreover, we also propose a detection feature pyramid loss function to more accurately restore object features. …”
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RT-DETR-Pro: An Enhanced RT-DETR Model for Visual Detection of Photovoltaic Module Defects by Yunliang Chen, Mingtao Shan, Wei Zhou, Bing Ma, Xun Mei

“…Firstly, an EMA (Efficient Multi-Scale Attention) module is integrated into the vanilla RT-DETR model to optimize feature representation by reshaping the channel and batch dimensions of feature maps. …”
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Maximizing Measurement Visual-Inertial Odometry for Low-Light Environment Through Online Image Pre-Processing by Suyong Lee, Hanyeol Lee, Chan Gook Park

“…This can adversely affect the extraction and tracking of feature points, resulting in insufficient measurements. …”
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Combining convolutional neural network with transformer to improve YOLOv7 for gas plume detection and segmentation in multibeam water column images by Wenguang Chen, Xiao Wang, Junjie Chen, Jialong Sun, Guozhen Zha

“…The emergence of convolutional neural networks (CNNs) alleviates this problem, but the local feature extraction of the convolutional operations, while capturing detailed information well, cannot adapt to the elongated morphology of the gas plume target, limiting the improvement of the detection and segmentation accuracy. …”
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Burned Area Segmentation in Optical Remote Sensing Images Driven by U-Shaped Multistage Masked Autoencoder by Yuxiang Fu, Wei Fang, Victor S. Sheng

“…The global branch inherits visual representation learning ability from the pretrained UMMAE and captures global contextual information from the input image, while the local branch extracts local spatial information at different scales. Features from two different branches are fused in the decoder for feature complementation, which improves feature discriminability and segmentation accuracy. …”
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GCB‐YOLO: A Lightweight Algorithm for Wind Turbine Blade Defect Detection by Zhiming Zhang, Chaoyi Dong, Ze Wei, Xiaoyan Chen, Weidong Zan, Yao Xue

“…Finally, the neck network was ultimately replaced with a bidirectional feature pyramid network (BiFPN) to optimize multiscale feature fusion, bolstering its ability to discern small defects. …”
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Tanggung Jawab Hukum bagi Konsumen atas Kerugian Layanan GrabFood oleh PT. Grab Teknologi Indonesia by Soya Putri Mirena, Imam Haryanto

“…The services provided by PT Grab in its GrabFood feature activities must refer to Article 4 of Law No. 8 of 1999 in order to protect consumer rights. …”
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Research on precision shaping technology of CVT for fairway cBN grinding wheel by Xiangguo QIN, Ziying ZHANG, Dongsheng TANG

“…MethodsBased on the technical problems existing in the current optical guided dressing method in engineering, this paper analyzes the principle of raceway forming grinding and the geometric feature structure of the raceway, and combs through the geometric accuracy control principle of the cBN grinding wheel in raceway grinding. …”
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Adaptive Image-Based Leader-Follower Approach of Mobile Robot with Omnidirectional Camera by Dejun Guo, Hesheng Wang, Weidong Chen, Xinwu Liang

“…This paper focuses on the problem of the adaptive image-based leader-follower formation control of mobile robot with on-board omnidirectional camera. …”
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Few-shot segmentation based on multi-level and cross-scale clustering by Shuai Yuan, Junhai Qiu, Hongxia Xu, Yan Zhang, Jiaxing Zhang

“…A novel method that consists of two modules is proposed: a multi-level fuzzy clustering guidance module and a cross-scale feature fusion module. The former module can extract image features in a class-independent feature space and fuse them with different scale information, while the latter module can reduce the information loss caused by cross-scale transmission. …”
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Binary Transformer Based on the Alignment and Correction of Distribution by Kaili Wang, Mingtao Wang, Zixin Wan, Tao Shen

“…To tackle this problem, the feature distribution alignment operation in binarization is investigated. …”
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Cross-device fault diagnosis method based on graph convolution and multi-sensor fusion by SUN Yuanshuai, KONG Fanqin, NIE Xiaoyin, XIE Gang

“…This method can model class labels, domain labels, and data feature structures.MethodsFirstly, a convolutional neural network was used to extract features from the input signal. …”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“…Secondly, the Generative Adversarial Networks is used to transfer the domain of night infrared gray image, and the image prediction results before and after migration are fused to solve the problem of weak target recognition ability in infrared image.Finally, the attention mechanism is added to the backbone feature extraction network to refine the feature map to improve the visual significance of snow leopard in RGB and infrared images, and the improved feature fusion network structure to integrate more effective information. …”
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A Method for Finding LR Fuzzy Eigenvectors of Real Symmetric Matrix by Xinyi Duan, Hangru Lin, Xiaobin Guo

“…In this paper, the calculation methods of the real eigenvalues and LR fuzzy eigenvectors of clear real symmetry matrices are deeply considered. The original fuzzy feature problem is extended by using the arithmetic algorithm of LR fuzzy numbers into a simple feature problem with a high-order clear real symmetry matrix. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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Nierozstrzygalność - drugie imię dekonstrukcji? by Elżbieta Winiecka

“…<span>The article focuses on the problem of undecidability - the main feature of literature according to Derrida. …”
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Pest detection in dynamic environments: an adaptive continual test-time domain adaptation strategy by Rui Fu, Shiyu Wang, Mingqiu Dong, Hao Sun, Mohammed Abdulhakim Al-Absi, Kaijie Zhang, Qian Chen, Liqun Xiao, Xuewei Wang, Ye Li

“…The MT-DAM integrates an object detection model with an image segmentation model, exchanging information through feature fusion at the feature extraction layer. During testing, test-time adaptation updates both models, continuing feature fusion during forward propagation. …”
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Using topological data analysis and machine learning to predict customer churn by Marcel Sagming, Reolyn Heymann, Maria Vivien Visaya

“…Abstract Customer churn is a common problem faced by many industries, including telecommunication industries. …”
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Time-Series Forecasting Method Based on Hierarchical Spatio-Temporal Attention Mechanism by Zhiguo Xiao, Junli Liu, Xinyao Cao, Ke Wang, Dongni Li, Qian Liu

“…A hierarchical feature fusion architecture is constructed to achieve multi-dimensional alignment of local spatial and global temporal features. …”
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