35,526 Result(s)
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Retraction Note: An Improved dynamic self-adaption cuckoo search algorithm based on collaboration between subpopulations
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A Multi-strategy Slime Mould Algorithm for Solving Global Optimization and Engineering Optimization Problems
Aiming at the problems of slow convergence, low accuracy, and easy to fall into local optimum of the slime mould algorithm (SMA), we propose an improved SMA (OJESMA). OJESMA improves the performance of the alg...
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A novel fusion feature imageization with improved extreme learning machine for network anomaly detection
As the complexity and quantity of network data continue to increase, accurate and efficient anomaly detection methods become critical. Deep learning-based methods are suitable for real-time detection because t...
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Deep reinforcement learning based mapless navigation for industrial AMRs: advancements in generalization via potential risk state augmentation
This article introduces a novel Deep Reinforcement Learning (DRL)-based approach for mapless navigation in Industrial Autonomous Mobile Robots, emphasizing advancements in generalization through Potential Risk...
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Achieving accurate and balanced regional electric vehicle charging load forecasting with a dynamic road network: a case study of Lanzhou City
Spatial and temporal predictions of electric vehicle (EV) charging loads provide a basis for further research on synergistic operation of road-vehicle-electricity networks with different attributes, which is i...
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Open AccessEsophagogastroscopy for predicting endoscopic ultrasonography T-stage by utilizing deep learning methods in esophageal cancer
Endoscopic ultrasonography (EUS) is commonly utilized in preoperative staging of esophageal cancer, however with additional pain and cost as well as adverse events. Meanwhile, the accuracy of EUS is highly dep...
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A new uncertain multi-objective rumor intervention model
Internet rumors have no factual basis, lack credibility, and can easily trigger social panic and group attacks. Measures to effectively intervene in rumors play a crucial role in curbing the spread of rumors. ...
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An expert method for defining the adaptation conditions of irrigated crops with the ecosystem of Northwestern China
The uncertain impacts of climate changes on the crop water requirements disarrange the on-farm balance of water supply and demand, thus here needs to adapt a crop** pattern to sustain the Northwestern China ...
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Open AccessLearning to sculpt neural cityscapes
We introduce a system that learns to sculpt 3D models of massive urban environments. The majority of humans live their lives in urban environments, using detailed virtual models for applications as diverse as ...
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CD-iNet: Deep Invertible Network for Perceptual Image Color Difference Measurement
Image color difference (CD) measurement, a crucial concept in color science and imaging technology, aims to quantify the perceived difference between two colors. Most widely recognized CD formulae are recommen...
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Multi-modal Prototypes for Open-World Semantic Segmentation
In semantic segmentation, generalizing a visual system to both seen categories and novel categories at inference time has always been practically valuable yet challenging. To enable such functionality, existin...
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On weighted threshold moment estimation of uncertain differential equations with applications in interbank rates analysis
Uncertainty theory is a branch of mathematics for modeling belief degrees. Within the framework of uncertainty theory, uncertain variable is used to represent quantities with uncertainty, and uncertain process...
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Industrial product surface defect detection via the fast denoising diffusion implicit model
In the age of intelligent manufacturing, surface defect detection plays a pivotal role in the automated quality control of industrial products, constituting a fundamental aspect of smart factory evolution. Con...
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Erratum to: A Comprehensive Review: Recent Developments of Biomimetic Sensors
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Class feature Sub-space for few-shot classification
Few-shot learning is used in the development of models that can acquire novel class concepts from limited training samples, facilitating rapid adaptation to novel, intricate, and varied tasks encountered in re...
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Open AccessXK-III: A Spherical Robot with Redundant Degrees of Freedom
The spherical robot XK-III, designed with redundant degrees of freedom, addresses the limitations of existing pendulum spherical robot structures by enhancing mobility and environmental adaptability. A nonline...
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Exploiting Diffusion Prior for Real-World Image Super-Resolution
We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution. Specifically, by employing our time-aware encoder, we can achieve ...
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Prediction of blast-hole utilization rate using structured nonlinear support vector machine combined with optimization algorithms
Blasting is the primary method for ultra-deep roadway engineering, which is facing the challenge of low footage caused by unsatisfactory blasting effects. Among all the evaluation indicators, the blast-hole ut...
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New characterizations of partial orders induced by a class of non-divisible t-norms
In this article, we deal with the algebraic structures of the partial orders induced by non-divisible t-norms. We first give a condition for the partial orders induced by non-divisible t-norms being a meet sem...
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Learning improvement of spiking neural networks with dynamic adaptive hyperparameter neurons
Spiking neural networks (SNNs) which use spiking neurons as a component, have shown substantial promise in simulating biological neuron mechanisms and saving computing power. However, preset or suboptimal hype...
