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Time Series
Examining and making predictions about the progress and evolution of data over time requires both long established and current techniques in data...
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Predicting the state of synchronization of financial time series using cross recurrence plots
Cross-correlation analysis is a powerful tool for understanding the mutual dynamics of time series. This study introduces a new method for predicting...
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Bayesian Personalized Sorting Based on Time Factors and Hot Recommendations
Aiming at the problems of strict preference judgment and cold start in Bayesian personalized ranking(BPR), an improved ranking model is proposed,...
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POI recommendation with queuing time and user interest awareness
Point-of-interest (POI) recommendation is a challenging problem due to different contextual information and a wide variety of human mobility...
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RTMDet-R2: An Improved Real-Time Rotated Object Detector
Object detection in remote sensing images is challenging due to the absence of visible features and variations in object orientation. Efficient...
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AAPL Forecasting Using Contemporary Time Series Models
Predicting the value of stock prices is separate from external investment exposure to the stock market. The aim of the article is to evaluate...
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AnIO: anchored input–output learning for time-series forecasting
In this work, the short-term electric load demand forecasting problem is addressed, proposing a method inspired by the use of anchors in object...
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Time-Series Analysis
Haksun Li, PhDa*
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Experimental and numerical demonstration of hierarchical time-delay reservoir computing based on cascaded VCSELs with feedback and multiple injections
In this paper, we propose and demonstrate experimentally and numerically a hierarchical time-delay optical reservoir computing (RC) system based on...
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A lightweight YOLOv8 integrating FasterNet for real-time underwater object detection
In this paper, we propose a underwater target detection method that optimizes YOLOv8s to make it more suitable for real-time and underwater...
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EMFANet: a lightweight network with efficient multi-scale feature aggregation for real-time semantic segmentation
In recent years, the performance of real-time semantic segmentation has increasingly become a research focus for real-time applications such as...
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Real-time object detection method based on YOLOv5 and efficient mobile network
The object detection algorithm YOLOv5, which is based on deep learning, experiences inefficiencies due to an overabundance of model parameters and an...
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Real-time human action prediction using pose estimation with attention-based LSTM network
Human action prediction in a live-streaming videos is a popular task in computer vision and pattern recognition. This attempts to identify activities...
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MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection
Accurate detection of pedestrian lanes is a crucial criterion for vision-impaired people to navigate freely and safely. The current deep learning...
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TD-LSTM: a time distributed and deep-learning-based architecture for classification of motor imagery and execution in EEG signals
One of the critical challenges in brain-computer interfaces is the classification of brain activities through the analysis of EEG signals. This paper...
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A generalized hardware architecture for real-time spiking neural networks
This article presents an area- and power-efficient hardware architecture for the brain-implantable spiking neural networks (SNNs). The proposed...
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Real-Time Monitoring Tool for SNN Hardware Architecture
Spiking Neural Networks (SNN) are characterized by their brain-inspired biological computing paradigm. Large-scale hardware platforms are reported,...
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Time-Aware QoS Web Service Selection Using Collaborative Filtering: A Literature Review
The large increase in the number of available Web services makes the selection of suitable services a big challenge. Several methods have been...
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FastBeltNet: a dual-branch light-weight network for real-time conveyor belt edge detection
Belt conveyors are widely used in multiple industries, including coal, steel, port, power, metallurgy, and chemical, etc. One major challenge faced...
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DAABNet: depth-wise asymmetric attention bottleneck for real-time semantic segmentation
With the increasing demand for the real-world applications such as autonomous driving and video surveillance, lightweight semantic segmentation...
