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Article
Multi-Modal Generative DeepFake Detection via Visual-Language Pretraining with Gate Fusion for Cognitive Computation
With the widespread adoption of deep learning, there has been a notable increase in the prevalence of multimodal deepfake content. These deepfakes pose a substantial risk to both individual privacy and the sec...
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Article
Dual-branch and triple-attention network for pan-sharpening
Pan-sharpening is a technique used to generate high-resolution multi-spectral (HRMS) images by merging high-resolution panchromatic (PAN) images with low-resolution multi-spectral (LRMS) images. Many existing ...
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Article
Towards automatically generating meal plan based on genetic algorithm
With the rising of the concept of balanced diet, more and more people pay attention to the healthy meal plans. However, a meal plan is usually difficult to meet people’s taste preferences and health standards ...
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Chapter and Conference Paper
Segmenting Key Clues to Induce Human-Object Interaction Detection
Two-stage HOI detectors have made great progress in training and inference, but still suffer from loss of original image features and ambiguous human-object relationships. To address the above issues, this pap...
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Chapter and Conference Paper
Attention and Time Perception Based Link Prediction in Dynamic Networks
There are numerous applications that could be modeled as networks and predicting their relationships within their evolution process is an important task
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Chapter and Conference Paper
Knowledge Tracing as Language Processing: A Large-Scale Autoregressive Paradigm
Knowledge tracing (KT) is the process of modelling students’ cognitive states to forecast their future academic performance, using their historical learning interactions as a reference. Recent scholarly invest...
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Chapter and Conference Paper
Multi-scale Contrastive Learning for Building Change Detection in Remote Sensing Images
Self-supervised contrastive learning (CL) methods can utilize large-scale label-free data to mine discriminative feature representations for vision tasks. However, most existing CL-based approaches focus on im...
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Chapter and Conference Paper
Automatic Lesson Plan Generation via Large Language Models with Self-critique Prompting
In this paper, we utilize the understanding and generative abilities of large language models (LLMs) to automatically produce customized lesson plans. This addresses the common challenge where conventional pla...
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Chapter and Conference Paper
Foreground and Background Separate Adaptive Equilibrium Gradients Loss for Long-Tail Object Detection
The current mainstream object detection methods usually tend to implement on datasets where the categories remain balanced, and have made great progress. However, in the presence of long-tail distribution, the...
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Article
Unsupervised person re-identification based on distribution regularization constrained asymmetric metric learning
In unsupervised person re-identification, the traditional asymmetric metric learning alleviates the bias of person images from different views. However, there still exists the issue that the features of the sa...
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Article
Open AccessMobility trajectory generation: a survey
Mobility trajectory data is of great significance for mobility pattern study, urban computing, and city science. Self-driving, traffic prediction, environment estimation, and many other applications require la...
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Article
Flow Learning Based Dual Networks for Low-Light Image Enhancement
The deep learning-based low-light image enhancement task aims to learn a map** that converts low-light images to normally exposed images by training with paired or unpaired datasets. Most of these existing m...
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Article
TIAR: Text-Image-Audio Retrieval with weighted multimodal re-ranking
Cross-modal retrieval has developed remarkably recently and received extensive attention as an essential method for multimodal interaction study. However, most existing models are limited to one of the applica...
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Article
Dynamic network link prediction based on random walking and time aggregation
Dynamic network link prediction has practical applications in many areas, such as social networks, traffic networks, biological networks, and citation networks. Because of its essential practical significance,...
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Article
FPANet: feature pyramid attention network for crowd counting
Crowd counting in congested scenarios is an essential yet challenging task in detecting abnormal crowd for contemporary urban planning. The counting accuracy has been significantly improved with the rapid deve...
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Article
Generative adversarial networks with adaptive learning strategy for noise-to-image synthesis
Generative adversarial networks (GANs) directly learn from an unknown real distribution through adversarial training. However, training the generator only by the feedback of the discriminator cannot make GANs ...
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Article
M2GCN: multi-modal graph convolutional network for modeling polypharmacy side effects
Treating patients with complex diseases or co-existing conditions by polypharmacy (i.e., the use of drug combination) is very common. However, due to drug-drug interactions, polypharmacy often results in unpre...
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Article
Open AccessA survey of urban visual analytics: Advances and future directions
Develo** effective visual analytics systems demands care in characterization of domain problems and integration of visualization techniques and computational models. Urban visual analytics has already achiev...
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Article
Learning a spatial-temporal symmetry network for video super-resolution
The video super-resolution (VSR) method is designed to estimate and restore high-resolution (HR) sequences from low-resolution (LR) input. For the past few years, many VSR methods with machine learning have be...
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Chapter and Conference Paper
The Transfer of Perceptual Learning Between First- and Second-Order Fine Orientation Discriminations
FirsT- and second-order systems have been proposed to explain visual information processing. With regard to the communications between the two systems, mixed results have been shown. The transfer of perceptual...