2,023 Result(s)
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Article
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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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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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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The concept information of graph granule with application to knowledge graph embedding
Knowledge graph embedding (KGE) has become one of the most effective methods for the numerical representation of entities and their relations in knowledge graphs. Traditional methods primarily utilise triple f...
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Air combat maneuver decision based on deep reinforcement learning with auxiliary reward
For air combat maneuvering decision, the sparse reward during the application of deep reinforcement learning limits the exploration efficiency of the agents. To address this challenge, we propose an auxiliary ...
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Article
Distribution-decouple learning network: an innovative approach for single image dehazing with spatial and frequency decoupling
Image dehazing methods face challenges in addressing the high coupling between haze and object feature distributions in the spatial and frequency domains. This coupling often results in oversharpening, color d...
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Open AccessSS-CRE: A Continual Relation Extraction Method Through SimCSE-BERT and Static Relation Prototypes
Continual relation extraction aims to learn new relations from a continuous stream of data while avoiding forgetting old relations. Existing methods typically use the BERT encoder to obtain semantic embeddings...
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Knowledge and separating soft verbalizer based prompt-tuning for multi-label short text classification
Multi-label Short Text Classification (MSTC) is a challenging subtask of Multi-Label Text Classification (MLTC) for tagging a short text with the most relevant subset of labels from a given set of labels. Rece...
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An adaptive joint optimization framework for pruning and quantization
Pruning and quantization are among the most widely used techniques for deep learning model compression. Their combined application holds the potential for even greater performance gains. Most existing works co...
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Multivariate time series anomaly detection via dynamic graph attention network and Informer
In the industrial Internet, industrial software plays a central role in enhancing the level of intelligent manufacturing. It enables the promotion of digital collaborative services. Effective anomaly detection...
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Article
Rapid density estimation of tiny pests from sticky traps using Qpest RCNN in conjunction with UWB-UAV-based IoT framework
Precision agriculture has long struggled with the surveillance and control of pests. Traditional methods for estimating pest density and distribution through manual reconnaissance are often time-consuming and ...
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Tripartite evolutionary game in the process of network attack and defense
At present, confrontations in cyberspace are becoming increasingly fierce, and network attacks and defenses have become the main form of confrontation between parties in cyberspace. The maximum benefit can be ...
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Article
Open AccessFL-GUARD: A Holistic Framework for Run-Time Detection and Recovery of Negative Federated Learning
Federated learning (FL) is a promising approach for learning a model from data distributed on massive clients without exposing data privacy. It works effectively in the ideal federation where clients share hom...
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English letter recognition based on adaptive optimization spiking neural P systems
The novel dynamic guider algorithm within the adaptive optimization spiking neural P system (AOSNPS) framework is employed to create an innovative English letter recognition algorithm. This algorithm utilizes ...
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Aerodynamic Performance of Three Flap** Wings with Unequal Spacing in Tandem Formation
To better understand the aerodynamic reasons for highly organized movements of flying organisms, the three-flap** wing system in tandem formation was studied numerically in this paper. Different from previou...
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Open AccessTemporally Consistent Enhancement of Low-Light Videos via Spatial-Temporal Compatible Learning
Temporal inconsistency is the annoying artifact that has been commonly introduced in low-light video enhancement, but current methods tend to overlook the significance of utilizing both data-centric clues and ...
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Open AccessLCTCS: Low-Cost and Two-Channel Sparse Network for Hyperspectral Image Classification
Using convolutional neural networks (CNNs) in classifying hyperspectral images (HSIs) has achieved quite good results in recent years. It is widely used in agricultural remote sensing, geological exploration, ...
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Position information encoding FPN for small object detection in aerial images
Small object detection in aerial images is a challenge in remote sensing. Recently, convolutional neural networks (CNNs) have succeeded by learning localized filters that embed relative spatial information but...
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Learning cooperative strategies in multi-agent encirclement games with faster prey using prior knowledge
Multi-agent encirclement with collision avoidance constitutes a common challenge in the multi-agent confrontation domain, wherein the focus lies in the development of cooperative strategies among agents. Previ...
