22,264 Result(s)
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Article
A general framework for improving cuckoo search algorithms with resource allocation and re-initialization
Cuckoo search (CS) has currently become one of the most favorable meta-heuristic algorithms (MHAs). In this article, a simple yet effective framework is proposed for CS algorithms to reinforce their performanc...
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Article
Combining core points and cluster-level semantic similarity for self-supervised clustering
Contrastive learning utilizes data augmentation to guide network training. This approach has attracted considerable attention for clustering, object detection, and image segmentation. However, previous studies...
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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...
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Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications
Knowledge Graph (KG) has attracted more and more companies’ attention for its ability to connect different types of data in meaningful ways and support rich data services. However, due to privacy concerns, dif...
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Road intersection detection using the YOLO model based on traffic signs and road signs
A road intersection is an area where more than two roads in different directions connect. It is a point of transition where the driver navigates and makes the decision, making it an area with a high risk for t...
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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 s...
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Article
Open AccessDynamic multi-label feature selection algorithm based on label importance and label correlation
Multi-label distribution is a popular direction in current machine learning research and is relevant to many practical problems. In multi-label learning, samples are usually described by high-dimensional featu...
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Recursive noisy label learning paradigm based on confidence measurement for semi-supervised depth completion
Depth completion is a critical task for extensive applications such as 3D reconstruction and object detection. Recent semi-supervised depth completion techniques based on Stereo-LiDAR fusion has gradually attr...
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Open AccessFederated quantum long short-term memory (FedQLSTM)
Quantum federated learning (QFL) can facilitate collaborative learning across multiple clients using quantum machine learning (QML) models, while preserving data privacy. Although recent advances in QFL span d...
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Unsupervised diffusion based anomaly detection for time series
Unsupervised anomaly detection aims to construct a model that effectively detects invisible anomalies by training and reconstruct normal data. While a significant amount of reconstruction-based methods has mad...
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Deep learning-based classification and application test of multiple crop leaf diseases using transfer learning and the attention mechanism
Crop diseases are among the major natural disasters in agricultural production that seriously restrict the growth and development of crops, threatening food security. Timely classification, accurate identifica...
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Article
Open AccessIlluminator: Image-based illumination editing for indoor scene harmonization
Illumination harmonization is an important but challenging task that aims to achieve illumination compatibility between the foreground and background under different illumination conditions. Most current studi...
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Open AccessA Lightweight Task-Agreement Meta Learning for Low-Resource Speech Recognition
Meta-learning has proven to be a powerful paradigm for transferring knowledge from prior tasks to facilitate the quick learning of new tasks in automatic speech recognition. However, the differences between la...
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Open AccessMultiple unmanned ship coverage and exploration in complex sea areas
This study addresses the complexities of maritime area information collection, particularly in challenging sea environments, by introducing a multi-agent control model for regional information gathering. Focus...
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A statistical mining from objective data to subjective knowledge based on granular perception
The relation between objectivity and subjectivity has been explored for many centuries in many aspects of fields. Most of the approaches used to study their relationship focus on the qualitative research, whic...
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Article
Advanced backtracking search for solving continuous optimization problems
This paper recommends develo** advanced backtracking search (ABS) to use single- and multi-vector mutation strategies to effectively enhance the backtracking search algorithm in solving a variety of optimiza...
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Article
MFDNet: Multi-Frequency Deflare Network for efficient nighttime flare removal
When light is scattered or reflected accidentally in the lens, flare artifacts may appear in the captured photographs, affecting the photographs’ visual quality. The main challenge in flare removal is to elimi...
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Undersampling based on generalized learning vector quantization and natural nearest neighbors for imbalanced data
Imbalanced datasets can adversely affect classifier performance. Conventional undersampling approaches may lead to the loss of essential information, while oversampling techniques could introduce noise. To add...
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Article
Towards effective urban region-of-interest demand modeling via graph representation learning
Identifying the region’s functionalities and what the specific Point-of-Interest (POI) needs is essential for effective urban planning. However, due to the diversified and ambiguity nature of urban regions, th...
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Article
Block diagonal representation learning with local invariance for face clustering
Facial data under non-rigid deformation are often assumed lying on a highly non-linear manifold. The conventional subspace clustering methods, such as Block Diagonal Representation (BDR), can only handle the h...
