Improvement of robust tensor principal component analysis based on generalized nonconvex approach
The problem of nonconvex robust tensor principal component analysis consists of recovering the low-rank and sparse part from a tensor corrupted by noise, which attracts a great deal of attention in a wide range of practical situations. However, ...
CMEFS: chaotic mapping-based mayfly optimization with fuzzy entropy for feature selection
Swarm intelligence algorithms availably settle the issue of feature selection for classification, whereas the Mayfly Optimization Algorithm (MOA) proposed in recent years has the superiority of high precision, concise structure, and effortless ...
A new uncertainty processing method for trajectory prediction
In many domains, trajectory prediction a crucial task. Uncertain information, such as complementary and correlated information between multiple features, complex interactive information, weather and temperature, increases the difficulty of ...
Probabilistic load forecasting based on quantile regression parallel CNN and BiGRU networks
In the dynamic smart grid landscape, accurate probabilistic forecasting of electric load is critical. This paper presents a novel 24-hour-ahead probabilistic load forecasting model by integrating quantile regression with a parallel convolutional ...
SMoTeF: Smurf money laundering detection using temporal order and flow analysis
Smurfing in financial networks is a popular fraud technique in which fraudsters inject their illegal money into the legitimate financial system. This activity is performed within a short period of time, with recurring transactions and multiple ...
Multistep traffic speed prediction from multiple time-scale spatiotemporal features using graph attention network
Traffic forecasting using deep learning represents a crucial aspect of intelligent transportation systems, carrying substantial implications for congestion reduction and efficient route planning. Despite its significance, accurately predicting ...
Progressive image compression for Gaussian mixture model quartile intervals
In this paper, we proposed a novel deep image coding and decoding model for GMMQI (Gaussian mixture model quartile intervals, GMMQI) and a variable rate bit allocation method to optimize the rate distortion performance and prioritize the ...
TAENet: transencoder-based all-in-one image enhancement with depth awareness
Recently, CNN-based all-in-one image enhancement methods have been proposed to solve multiple image degradation tasks. However, these CNN-based methods usually have two limitations. One limitation is that they usually design a specific encoder for ...
Two guidance joint network based on coarse map and edge map for camouflaged object detection
Camouflaged object detection (COD) entails identifying objects in an image that blend with the background. However, most traditional COD methods have not comprehensively considered the information provided by the overall region and edges of the ...
