Yingkun Hou

Block‐Extraction and Haar Transform Based Linear Singularity Representation for Image Enhancement

Seong-Whan Lee, Dinggang Shen, Xiaobo Qu, Guanghai Liu et autres

In this paper, we develop a novel linear singularity representation method using spatial K‐neighbor block‐extraction and Haar transform (BEH). Block‐extraction provides a group of image blocks with similar (generally smooth) backgrounds but different image edge locations. An interblock Haar transform is then …

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The TikTok miracle: cracking the code of TikTok’s platform strategy

Yingkun Hou, Yiying Zhu

Purpose This study decodes the winning platform strategies behind TikTok's rapid rise in the social media ecosystem, aiming to provide generalizable insights for companies in the platform economy. It explores how TikTok overcame the formidable network effects of dominant platforms like Meta …

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DCLMD: dynamic clustering and label mapping distribution for constructing in-context learning demonstrations

Yongping Du, Qi Zhang, Shaojun Fu, Yingkun Hou et autres

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A novel commonsense reasoning method based on heterogeneous knowledge fusion and adversarial training

Yongping Du, Qi Zhang, Jingya Yan, Yingkun Hou et autres

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Pixel-Level Non-Local Method-Based Depth Image Inpainting

Yingkun Hou, Hao Hou, Bin Feng, Mengyu Liu

Each pixel intensity value in a depth image represents the depth information in the scene. However, during the generation of depth images, some important information may be lost in the form of pieces, which can seriously impact subsequent applications, such as computer …

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Study of conveyor belt deviation detection based on improved YOLOv8 algorithm

Yunfeng Ni, Haixin Cheng, Yingkun Hou, Ping Guo

Conveyor belt deviation is a commmon and severe type of fault in belt conveyor systems, often resulting in significant economic losses and potential environment pollution. Traditional detection methods have obvious limitations in fault localization precision and analysis accuracy, unable to meet the …

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Research on Computer Vision Image Classification System Based on Deep Learning

Hongxiang Yang, Yingkun Hou

This paper uses Python and TensorFlow framework. Using low power computer Raspberry as model computing platform and sorting processing platform, the damaged parts identification system based on computer vision technology and deep learning technology is realized. Multi-scale interactive iterative learning algorithm is …

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Semi-Cycled Generative Adversarial Networks for Real-World Face Super-Resolution

Hao Hou, Jun Xu, Yingkun Hou, Xiaotao Hu et autres

Real-world face super-resolution (SR) is a highly ill-posed image restoration task. The fully-cycled Cycle-GAN architecture is widely employed to achieve promising performance on face SR, but is prone to produce artifacts upon challenging cases in real-world scenarios, since joint participation in the …

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PNCS: Pixel-Level Non-Local Method Based Compressed Sensing Undersampled MRI Image Reconstruction

Hao Hou, Yuchen Shao, Yang Geng, Yingkun Hou et autres

Compressed sensing magnetic resonance imaging (CS-MRI) has made great progress in speeding up MRI imaging. The existing non-local self-similarity (NSS) prior based CS-MRI models mainly take similar image patches as the processing objects, this patch-level non-local sparse representation method can not make …

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A Method for Plant Diseases Detection Based on Transfer Learning and Data Enhancement

Jing Liu, Guofeng Zhang, Bin Feng, Yingkun Hou et autres

With the wide application of deep learning in the field of agriculture, how to quickly and accurately identify and process structured and unstructured monitoring data to support intelligent decision-making has become an important research direction in the field of intelligent agriculture. In …

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Semi-Cycled Generative Adversarial Networks for Real-World Face Super-Resolution

Hao Hou, Jun Xu, Yingkun Hou, Xiaotao Hu et autres

Real-world face super-resolution (SR) is a highly ill-posed image restoration task. The fully-cycled Cycle-GAN architecture is widely employed to achieve promising performance on face SR, but prone to produce artifacts upon challenging cases in real-world scenarios, since joint participation in the same …

Latent low-rank representation with sparse consistency constraint for infrared and visible image fusion

Tiwei Tao, Ming-Xia Liu, Yingkun Hou, Pengfei Wang et autres

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