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Dual-band low-light image enhancement
Most of the existing low-light image enhancement algorithms are designed for one kind of low-light image, which cannot effectively handle the...
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Spectral normalization and dual contrastive regularization for image-to-image translation
Existing image-to-image (I2I) translation methods achieve state-of-the-art performance by incorporating the patch-wise contrastive learning into...
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Dual visual align-cross attention-based image captioning transformer
Region-based features widely used in image captioning are typically extracted using object detectors like Faster R-CNN. However, the approach has a...
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Dual-context aggregation for universal image matting
Natural image matting aims to estimate the alpha matte of the foreground from a given image. Various approaches have been explored to address this...
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Modified dual attention triplet-supervised hashing network for image retrieval
In view of the problems of insufficient feature extraction and ineffective capture of correlation between deep features in existing image retrieval...
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Dual enhanced semantic hashing for fast image retrieval
As a highly promising technique in the field of similarity search, the hashing-based image retrieval algorithm has received continued attention in...
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Advancing image captioning with V16HP1365 encoder and dual self-attention network
Image captioning generates textual description from the corresponding input image with the help of computer vision and natural language processing....
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Image splicing manipulation location by multi-scale dual-channel supervision
The swift growth of diverse editing software has resulted in image splicing manipulation becoming more complex, the discovery of a meticulously...
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Full reference image quality assessment based on dual-space multi-feature fusion
At present, the majority of techniques for assessing image quality are limited to extracting features from an image in a single space. This paper...
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Exploring homogeneity index modification on dual-HDR-image-based reversible data hiding
Dual-image-based reversible data hiding refers to generating two output images after a secret message has been embedded in an original image...
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Candros optimization algorithm based dual attention LieNet model for low light image enhancement
The images taken in the low-light environment appear dark and possess low visual quality due to inadequate light exposure, which influences the image...
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Dual-Stream CoAtNet models for accurate breast ultrasound image segmentation
The CoAtNet deep neural model has been shown to achieve state-of-the-art performance by stacking convolutional and self-attention layers. In...
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Dual-Fisheye Image Stitching via Unsupervised Deep Learning
Constructing panoramic images from a dual-fisheye lens has been increasingly used along with the recent booming of new computer vision applications,...
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Dual-attention-transformer-based semantic reranking for large-scale image localization
The large-scale image-based localization (IBL) problem involves matching a query image with a database image to determine the geolocation of the...
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Unsupervised learning based dual-branch fusion low-light image enhancement
Distortion-free enhancement on images captured under low-light conditions has always been a challenging problem in computer vision. Although many...
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Feature channel interaction long-tailed image classification model based on dual attention
In the real world, the data distribution often presents a long tail distribution, and the imbalance of data will lead to the model learning bias to...
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Fault-tolerant quantum algorithm for dual-threshold image segmentation
The intrinsic high parallelism and entanglement characteristics of quantum computing have made quantum image processing techniques a focus of great...
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FAColorGAN: a dual-branch generative adversarial network for near-infrared image colorization
In addressing the issues of detail loss and poor robustness in near-infrared (NIR) image colorization tasks, this paper introduces a dual-branch...
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Dual parallel multi-scale residual overlay network for single-image rain removal
Rain not only degrades the perceptual image quality, but also destroys the visibility of the scene, which affects the computer vision algorithms’...
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Attention based dual UNET network for infrared and visible image fusion
How to accurately extract the effective information and profile features of source images has been a difficult problem in the domain of infrared and...
