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Article
Multi-scale saliency features fusion model for person re-identification
Person re-identification mainly uses computer vision technology to determine whether there are specific pedestrians in the image or video. Belong to cross-device retrieval images, due to the changing style of ...
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Article
Attention-based multi-scale recursive residual network for low-light image enhancement
Aiming at the problems of color distortion, low image processing efficiency, rich context information, spatial information imbalance in the current low-light image enhancement algorithm based on a convolutiona...
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Article
Layer similarity guiding few-shot Chinese style transfer
Few-shot text style transfer faces two main challenges: The first challenge is the limited availability of reference style text, while the second challenge is the varying degrees of differences between the sty...
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Article
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 the head class. To address the influence of long tail distrib...
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Article
Incremental image retrieval method based on feature perception and deep hashing
How to propose an image retrieval algorithm with adaptable model and wide range of applications for large-scale datasets has become a critical technical problem in current image retrieval. This paper proposed ...
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Article
Small target detection algorithm for printing defects detection based on context structure perception and multi-scale feature fusion
Small target detection is an important research direction in the field of computer vision, which is widely used in popular fields such as industrial defect detection, satellite remote sensing image detection. ...
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Article
No-reference image quality assessment of multi-level residual feature augmentation
No-reference image quality assessment (NR-IQA) has a wide range of application scenarios and occupies an important position in the field of digital image processing. In this paper, we propose a multi-level fea...
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Article
Coordinate feature fusion networks for fine-grained image classification
Learning feature representations from discriminative local features plays a key role in fine-grained classification, but many methods tend to focus only on salient features in images and ignore most latent fea...
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Article
Pedestrian reidentification based on multiscale convolution feature fusion
The current pedestrian reidentification method based on convolutional neural networks still cannot solve the problems of pedestrian posture change, occlusion and background clutter. Many people use local featu...
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Article
A deep multi-feature distance metric learning method for pedestrian re-identification
Consider the problem that handcrafted features are limited by not being directly applicable to practical problems. Additionally, the deep convolution feature is a high-dimensional feature, and if it is directl...
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Chapter and Conference Paper
A Novel Blind JPEG Image Quality Assessment Based on Blockiness and the Low Frequency Feature in DCT Domain
Blind image quality assessment metrics play an important role in the field of image processing. Blind image quality assessment methods, which are specific to a given type of distortion, are very popular for di...
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Chapter and Conference Paper
Image Retrieval Based on the Multi-index and Combination of Several Features
Local interest points serve as elementary building blocks in many image retrieval algorithms, and most of them exploit the local volume features using a Bag of Feature (BOF) model. However, the model ignores s...
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Chapter and Conference Paper
BOF Image/Video Retrieval Model with Global Feature
Local interest points serve as an elementary building block in many video retrieval algorithms, and most of them exploit the local volume features using a Bag of Features (BOF) representation. Such representat...
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Chapter and Conference Paper
A New Parallel Hierarchical K-Means Clustering Algorithm for Video Retrieval
The K-means clustering algorithm has been widely adopted to build vocabulary in image retrieval. But, the speed and accuracy of K-means still need to be improved. In the manuscript, we propose a New Parallel H...
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Article
An efficient content based video copy detection using the sample based hierarchical adaptive k-means clustering
Content-based video copy detection (CBCD) is very important for video copyright protection in view of the growing popularity of video sharing websites, which deals with not only whether a copy occurs in a quer...