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Multi-scale cross-fusion for arbitrary scale image super resolution
Deep convolutional neural networks (CNNs) have great improvements for single image super resolution (SISR). However, most of the existing SISR...
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Crowd Counting based on Multi-level Multi-scale Feature
Crowd counting has drawn more and more attention for its significance in reality application. However, it’s still a challenging task because of scale...
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Adversarial multi-image steganography via texture evaluation and multi-scale image enhancement
Multi-image steganography refers to a data-hiding scheme where a user tries to hide confidential messages within multiple images. Different from the...
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MLANet: multi-level attention network with multi-scale feature fusion for crowd counting
Estimating the population in a given scene is a process known as crowd counting. The field has recently garnered significant attention, and many...
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2MGAS-Net: multi-level multi-scale gated attentional squeezed network for polyp segmentation
Accurate segmentation of colon polyps in endoscopic images is crucial for early colorectal cancer diagnosis and treatment planning. However,...
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3D Human pose estimation from video via multi-scale multi-level spatial temporal features
In this paper, we present an innovative framework for 2D-to-3D human pose estimation from video, harnessing the power of multi-scale multi-level...
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MEDMCN: a novel multi-modal EfficientDet with multi-scale CapsNet for object detection
Object detection in real-world scenarios with multi-modal inputs is crucial for some safety-critical systems, such as autonomous driving, security...
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Multi-view Self-supervised Learning and Multi-scale Feature Fusion for Automatic Speech Recognition
To address the challenges of the poor representation capability and low data utilization rate of end-to-end speech recognition models in deep...
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Multi-scale decision systems with test cost and applications to three-way multi-attribute decision-making
In real life, humans often need to deal with data hierarchically structured at different levels. The more detailed data that is collected, the...
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Multi-scale hash encoding based neural geometry representation
Recently, neural implicit function-based representation has attracted more and more attention, and has been widely used to represent surfaces using...
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Person re-identification based on multi-scale feature fusion and multi-attention mechanism
Person re-identification is an image retrieval technique for person in real scenes. Due to factors such as camera angle, lighting, and occlusion,...
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Retinal artery/vein classification by multi-channel multi-scale fusion network
The automatic artery/vein (A/V) classification in retinal fundus images plays a significant role in detecting vascular abnormalities and could speed...
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EnCoSum: enhanced semantic features for multi-scale multi-modal source code summarization
Code summarization aims to generate concise natural language descriptions for a piece of code, which can help developers comprehend the source code....
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MS-RAFT+: High Resolution Multi-Scale RAFT
Hierarchical concepts have proven useful in many classical and learning-based optical flow methods regarding both accuracy and robustness. In this...
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Noise-aware progressive multi-scale deepfake detection
The proliferation of fake images generated by deepfake techniques has significantly threatened the trustworthiness of digital information, leading to...
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Multi-scale adaptive attention-based time-variant neural networks for multi-step time series forecasting
Time series analysis is the process of exploring and analyzing past trends to predict future events for any given time interval. Powered by recent...
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Multi-scale-ResUNet: an improve u-net with multi-scale attention and hybrid dilation for medical image segmentation
The liver is one of the largest and most important organs in the human body. It maintains important life activities and is also one of the organs...
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Multi-scale pooling learning for camouflaged instance segmentation
Camouflaged instance segmentation (CIS) focuses on handling instances that attempt to blend into the background. However, existing CIS methods...
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Coarse-to-fine multi-scale attention-guided network for multi-exposure image fusion
In recent years, deep learning networks have achieved prominent success in the field of multi-exposure image fusion. However, it is still challenging...
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Mitigate the scale imbalance via multi-scale information interaction in small object detection
The scale imbalance of the backbone and the neck is the main reason for the inferior accuracy of small object detection when using the general object...
