In this paper, a frog-shaped ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna is proposed for 5G applications in the n77, n78, n79, and 6 GHz bands with a compact antenna structure of 31 × 55 &#...
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Image captioning has seen significant research efforts over the last *** goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically *** real-world appl...
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Image captioning has seen significant research efforts over the last *** goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically *** real-world applications rely on image captioning,such as helping people with visual impairments to see their *** formulate a coherent and relevant textual description,computer vision techniques are utilized to comprehend the visual content within an image,followed by natural language processing *** approaches and models have been developed to deal with this multifaceted *** models prove to be stateof-the-art solutions in this *** work offers an exclusive perspective emphasizing the most critical strategies and techniques for enhancing image caption *** than reviewing all previous image captioning work,we analyze various techniques that significantly improve image caption generation and achieve significant performance improvements,including encompassing image captioning with visual attention methods,exploring semantic information types in captions,and employing multi-caption generation ***,advancements such as neural architecture search,few-shot learning,multi-phase learning,and cross-modal embedding within image caption networks are examined for their transformative *** comprehensive quantitative analysis conducted in this study identifies cutting-edgemethodologies and sheds light on their profound impact,driving forward the forefront of image captioning technology.
Deep Hashing is a technique used for retrieving images on a large-scale, encoding the latent code of images into binary codes, which significantly reduces computational and storage costs in image retrieval. This enabl...
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Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced *** management strategies(EMSs)that coordinate and control different energy sources ...
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Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced *** management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle *** study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power *** DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action *** often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing ***,these algorithms suffer from low sample ***,these factors contribute to convergence difficulties,low learning efficiency,and *** address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience ***,the correspondingMarkovDecision Process(MDP)is ***,an EMSbased on the improvedDRLmodel is *** simulation experiments are conducted against rule-based,optimization-based,andDRL-based *** proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global *** the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 *** to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%
With advancements in technology, the study of data hiding (DH) in images has become more and more important. In this paper, we introduce a novel data hiding scheme that employs a voting strategy to predict pixels base...
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Simulated Moving Bed (SMB) chromatographic separation technology is an innovative method that combines traditional fixed-bed adsorption operation with real moving bed (TMB) chromatographic separation technology. In or...
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UAV-based object detection is rapidly expanding in both civilian and military applications,including security surveillance,disaster assessment,and border ***,challenges such as small objects,occlusions,complex backgro...
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UAV-based object detection is rapidly expanding in both civilian and military applications,including security surveillance,disaster assessment,and border ***,challenges such as small objects,occlusions,complex backgrounds,and variable lighting persist due to the unique perspective of UAV *** address these issues,this paper introduces DAFPN-YOLO,an innovative model based on YOLOv8s(You Only Look Once version 8s).Themodel strikes a balance between detection accuracy and speed while reducing parameters,making itwell-suited for multi-object detection tasks from drone perspectives.A key feature of DAFPN-YOLO is the enhanced Drone-AFPN(Adaptive Feature Pyramid Network),which adaptively fuses multi-scale features to optimize feature extraction and enhance spatial and small-object *** leverage Drone-AFPN’smulti-scale capabilities fully,a dedicated 160×160 small-object detection head was added,significantly boosting detection accuracy for small *** the backbone,the C2f_Dual(Cross Stage Partial with Cross-Stage Feature Fusion Dual)module and SPPELAN(Spatial Pyramid Pooling with Enhanced LocalAttentionNetwork)modulewere *** components improve feature extraction and information aggregationwhile reducing parameters and computational complexity,enhancing inference ***,Shape-IoU(Shape Intersection over Union)is used as the loss function for bounding box regression,enabling more precise shape-based object *** results on the VisDrone 2019 dataset demonstrate the effectiveness *** to YOLOv8s,the proposedmodel achieves a 5.4 percentage point increase inmAP@0.5,a 3.8 percentage point improvement in mAP@0.5:0.95,and a 17.2%reduction in parameter *** results highlight DAFPN-YOLO’s advantages in UAV-based object detection,offering valuable insights for applying deep learning to UAV-specific multi-object detection tasks.
Older adults are often underserved and marginalized in technology engagement due to their reluctance and the barriers they face in adopting and engaging with mainstream technology. However, Pinxiaoquan, a social featu...
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Multi-image steganography refers to a data-hiding scheme where a user tries to hide confidential messages within multiple images. Different from the traditional steganography which only requires the security of an ind...
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The sharing of encrypted data in cloud computing is an essential functionality with countless applications in our everyday life. However, the issue of how to securely, efficiently and flexibly share encrypted data in ...
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