Visual information decoding aims to infer the visual content perceived by a subject based on their brain responses, representing a cutting-edge area of neuroscience research. Functional magnetic resonance imaging (fMR...
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To address the prevalent issue of impulsive buying behavior in the e-commerce environment, this study introduces a personalized online shopping recommendation system aimed at the short-term improvement of shopping imp...
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BdSL (Bangla Sign Language) is a language in its own right, with its own grammar, syntax, and rules for word order. There are 36 alphabets in the Bangla sign language (BdSL), some of which have pretty similar characte...
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Reinforcement learning has traditionally been studied with exponential discounting or the average reward setup, mainly due to their mathematical tractability. However, such frameworks fall short of accurately capturin...
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Vision Studio aims to utilize a diverse range of modern deep learning and computer vision principles and techniques to provide a broad array of functionalities in image and video processing. Deep learning is a distinc...
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In Internet of Things(loT),data sharing among different devices can improve manufacture efficiency and reduce workload,and yet make the network systems be more vulnerable to various intrusion *** has been realistic de...
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In Internet of Things(loT),data sharing among different devices can improve manufacture efficiency and reduce workload,and yet make the network systems be more vulnerable to various intrusion *** has been realistic demand to develop an efficient intrusion detection algorithm for connected *** of existing intrusion detection methods are trained in a centralized manner and are incapable to identify new unlabeled attack *** this paper,a distributed federated intrusion detection method is proposed,utilizing the information contained in the labeled data as the prior knowledge to discover new unlabeled attack ***,the blockchain technique is introduced in the federated learning process for the consensus of the entire *** results are provided to show that our approach can identify the malicious entities,while outperforming the existing methods in discovering new intrusion attack types.
Vehicle Color Recognition(VCR)plays a vital role in intelligent traffic management and criminal investigation ***,the existing vehicle color datasets only cover 13 classes,which can not meet the current actual ***,alt...
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Vehicle Color Recognition(VCR)plays a vital role in intelligent traffic management and criminal investigation ***,the existing vehicle color datasets only cover 13 classes,which can not meet the current actual ***,although lots of efforts are devoted to VCR,they suffer from the problem of class imbalance in *** address these challenges,in this paper,we propose a novel VCR method based on Smooth Modulation Neural Network with Multi-Scale Feature Fusion(SMNN-MSFF).Specifically,to construct the benchmark of model training and evaluation,we first present a new VCR dataset with 24 vehicle classes,Vehicle Color-24,consisting of 10091 vehicle images from a 100-hour urban road surveillance ***,to tackle the problem of long-tail distribution and improve the recognition performance,we propose the SMNN-MSFF model with multiscale feature fusion and smooth *** former aims to extract feature information from local to global,and the latter could increase the loss of the images of tail class instances for training with ***,comprehensive experimental evaluation on Vehicle Color-24 and previously three representative datasets demonstrate that our proposed SMNN-MSFF outperformed state-of-the-art VCR *** extensive ablation studies also demonstrate that each module of our method is effective,especially,the smooth modulation efficiently help feature learning of the minority or tail *** Color-24 and the code of SMNN-MSFF are publicly available and can contact the author to obtain.
Data interoperability is a crucial requirement in IoT to improve services and enhance business opportunities and innovation. Integrating synergetic applications with heterogeneous data formats is a critical issue that...
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In an ever-changing car market, it is still difficult to choose the best car from a wide range of options. 'AUTOGENIE' offers an innovative solution to this problem combining matrix factorization, collaborativ...
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Aiming at the low accuracy and missed detections of existing deep learning models for underwater marine product recognition in complex ocean environments, this paper proposes an improved network based on the YOLOv5 mo...
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