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Article
RaSTFormer: region-aware spatiotemporal transformer for visual homogenization recognition in short videos
With the surge in network traffic, the homogenization of short video content is becoming increasingly prominent, resulting in low-quality entertainment due to proliferation and infringement. Therefore, recogni...
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Article
Open AccessMCAD: Multi-classification anomaly detection with relational knowledge distillation
With the wide application of deep learning in anomaly detection (AD), industrial vision AD has achieved remarkable success. However, current AD usually focuses on anomaly localization and rarely investigates a...
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Article
HDUD-Net: heterogeneous decoupling unsupervised dehaze network
Haze reduces the imaging effectiveness of outdoor vision systems, significantly degrading the quality of images; hence, reducing haze has been a focus of many studies. In recent years, decoupled representation...
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Article
FATE: a three-stage method for arithmetical exercise correction
As the number of primary students rapidly rises, the highly repetitive task of correcting arithmetical exercises consumes much time for teachers and hinders them from concentrating more on the growth of studen...
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Article
Open AccessImproving unified named entity recognition by incorporating mention relevance
Named entity recognition (NER) is a fundamental task for natural language processing, which aims to detect mentions of real-world entities from text and classifying them into predefined types. Recently, resear...
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Article
EduNER: a Chinese named entity recognition dataset for education research
A high-quality domain-oriented dataset is crucial for the domain-specific named entity recognition (NER) task. In this study, we introduce a novel education-oriented Chinese NER dataset (EduNER). To provide re...
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Article
A multi-sensor feature fusion network model for bearings grease life assessment in accelerated experiments
This paper presents a multi-sensor feature fusion (MSFF) neural network comprised of two inception layer-type multiple channel feature fusion (MCFF) networks for both inner-sensor and cross-sensor feature fusi...
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Article
A deep learning framework for detecting and localizing abnormal pedestrian behaviors at grade crossings
This paper presents a deep learning-based framework to detect and localize the pedestrians’ anomaly behaviors in videos captured at the grade crossing. A skeleton detection and tracking algorithm are employed ...
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Article
SiamOA: siamese offset-aware object tracking
Object tracking task can be divided into two subtasks: classification and regression. Some state-of-the-art methods utilize classification score and quality estimation score to select proposal box. However, th...
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Article
TF-SOD: a novel transformer framework for salient object detection
Most of existing salient object detection models are based on fully convolutional network (FCN), which learn multi-scale/level semantic information through convolutional layers to obtain high-quality predicted...
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Article
An improved method for sink node deployment in wireless sensor network to big data
Wireless sensor network (WSNs) technology and Internet technology penetrate and extend each other. It is a good way for physical changes of objects, state recognition and data collection, and becomes an import...
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Article
Brain stroke lesion segmentation using consistent perception generative adversarial network
The state-of-the-art deep learning methods have demonstrated impressive performance in segmentation tasks. However, the success of these methods depends on a large amount of manually labeled masks, which are e...
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Article
Correction to: A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings
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Article
A joint model for entity and relation extraction based on BERT
In recent years, as the knowledge graph has attained significant achievements in many specific fields, which has become one of the core driving forces for the development of the internet and artificial intelli...
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Article
A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings
This paper presents a deep learning-assisted framework to estimate the decongestion time at the grade crossing, and its key novelty lies in a differential approach to address the challenge associated with data...
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Article
Dual temporal convolutional network for single-lead fibrillation waveform extraction
The f-wave extraction (FE) is essential for analysis of atrial fibrillations. However, the state-of-the-art FE methods are model-based, and they cannot well adapt to the QRST complexes with high morphological ...
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Article
A dynamic routing optimization problem considering joint delivery of passengers and parcels
With the rapid development of e-commerce, last-mile delivery optimization is important for reduction in logistics cost of e-business enterprises. However, the complex road network structure in various cities m...
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Article
Blind source separation for the analysis sparse model
Sparsity of the signal has been shown to be very useful for blind source separation (BSS) problem which aims at recovering unknown sources from their mixtures. In this paper, we propose a novel algorithm based...
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Article
A machine learning-based scheme for the security analysis of authentication and key agreement protocols
This paper proposes a novel machine learning-based scheme for the automatic analysis of authentication and key agreement protocols. Considering the traditional formal protocol analysis schemes, their analysis ...
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Article
Audiovisual cross-modal material surface retrieval
Cross-modal retrieval is developed rapidly because it can process the data among different modalities. Aiming at solving the problem that the text and image sometimes cannot perform the true and accurate analy...