<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[wujl]]></title><description><![CDATA[wujl]]></description><link>https://siplab.wixsite.com/wujl/research-blog</link><generator>RSS for Node</generator><lastBuildDate>Sun, 01 Nov 2026 10:13:49 GMT</lastBuildDate><atom:link href="https://siplab.wixsite.com/wujl/blog-feed.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[A Novel Fatigue Detection Method for Table Tennis Specific Aerobic Testing Using Residual-Attention-Based FinePOSE 3D Human Pose Estimation]]></title><link>https://siplab.wixsite.com/wujl/post/a-novel-fatigue-detection-method-for-table-tennis-specific-aerobic-testing-using-residual-attention</link><guid isPermaLink="false">692b9fe160ee78866f1ec897</guid><pubDate>Sun, 30 Nov 2025 01:37:40 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_81620b0c06a44f419f8f3b4c9b16bd7c~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[An Automatic Segmentation and Highlight Extraction Method for Table Tennis Videos Using The Human-Parsing Based Bimodal Deep Neural Networks]]></title><link>https://siplab.wixsite.com/wujl/post/an-automatic-segmentation-and-highlight-extraction-method-for-table-tennis-videos-using-the-human-pa</link><guid isPermaLink="false">692b9f9bce8000f2f4b9f5a7</guid><pubDate>Sun, 30 Nov 2025 01:36:33 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_6a8e852372484beaa6a15ae27413a1d5~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[The Trajectory Tracking and Tactical Analysis for Table Tennis Videos Using Deep Learning Neural Net]]></title><link>https://siplab.wixsite.com/wujl/post/the-trajectory-tracking-and-tactical-analysis-for-table-tennis-videos-using-deep-learning-neural-net</link><guid isPermaLink="false">6472c65a7bf716e2118578cf</guid><pubDate>Sun, 28 May 2023 03:11:24 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_4b81ee4869fb45bd90db56f6414ff241~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[Medical Image Segmentation]]></title><link>https://siplab.wixsite.com/wujl/post/medical-image-segmentation</link><guid isPermaLink="false">6472c613eec3a809a38439e5</guid><pubDate>Sun, 28 May 2023 03:10:14 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_f73926b166794cb6866d1356111371a5~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[Hand-Eye Calibration Using Computer Vision Approach]]></title><link>https://siplab.wixsite.com/wujl/post/hand-eye-calibration-using-computer-vision</link><guid isPermaLink="false">5e7d48d979d6da002d7a94ea</guid><pubDate>Fri, 27 Mar 2020 00:34:27 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_35683b4b91154ce4ba6c8c555667ba91~mv2.png/v1/fit/w_633,h_717,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[A Learning-based Image Enhancement Method Using Cycle GAN and Adaptive Gamma Correction]]></title><description><![CDATA[With the development of mobile phone cameras, more and more people use their mobile phones to take daily photos. However, due to the...]]></description><link>https://siplab.wixsite.com/wujl/post/a-learning-based-image-enhancement-method-using-cycle-gan-and-adaptive-gamma-correction</link><guid isPermaLink="false">5df49ac9dd2a2a001773459a</guid><pubDate>Sat, 14 Dec 2019 08:19:47 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_d0b81e48a97444149e8f866fb01e4dc2~mv2.png/v1/fit/w_1000,h_818,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[Using deep learning technology &#38; video visual technology in the analysis of table tennis competition]]></title><description><![CDATA[During competitive ball games, people usually use the information system to collect skill-related data according to players’ performance....]]></description><link>https://siplab.wixsite.com/wujl/post/using-deep-learning-technology-video-visual-technology-in-the-analysis-of-table-tennis-competition</link><guid isPermaLink="false">5df4458626d25100177547b6</guid><pubDate>Sat, 14 Dec 2019 02:27:45 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_291c1f0bd9aa4c9daa2bfb1155f04534~mv2.png/v1/fit/w_1000,h_758,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[A Robust Music Auto-Tagging Technique Using Audio Fingerprinting and Deep Convolutional Neural Netwo]]></title><description><![CDATA[Music tags are a set of descriptive keywords that convey high-level information about a music clip, such as emotions(sadness, happiness),...]]></description><link>https://siplab.wixsite.com/wujl/post/a-robust-music-auto-tagging-technique-using-audio-fingerprinting-and-deep-convolutional-neural-netwo</link><guid isPermaLink="false">5b8ef3bfad43b60021565fb1</guid><pubDate>Tue, 04 Sep 2018 21:07:21 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_ef54d43d2ecc4185a2c84897abd69dac~mv2_d_1200_1230_s_2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[A Fast and Robust Audio Fingerprinting Method Using Constant Q Transform and Clustering Strategy
]]></title><description><![CDATA[Audio fingerprints help to identify the audio content from database. Audio fingerprinting is to match an audio recording from audio...]]></description><link>https://siplab.wixsite.com/wujl/post/a-fast-and-robust-audio-fingerprinting-method-using-constant-q-transform-and-clustering-strategy</link><guid isPermaLink="false">5b8ef13ed5fe1e0014de28bb</guid><pubDate>Tue, 04 Sep 2018 20:57:25 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_e84ec799c5074bf083ab95644673fdca~mv2.jpg/v1/fit/w_1000,h_870,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[A Deep-Learning-Based Face and License Plate Detection Technique for The Privacy Protection in Hospi]]></title><description><![CDATA[In recent years, with the photographic lens becoming the basic equipment of the handheld device, various photos taken in public, whether...]]></description><link>https://siplab.wixsite.com/wujl/post/a-deep-learning-based-face-and-license-plate-detection-technique-for-the-privacy-protection-in-hospi</link><guid isPermaLink="false">5b8542b99c19c8003120eb1d</guid><pubDate>Tue, 28 Aug 2018 12:42:31 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_bd58eeaace4a4807b39e1dce9b109df3~mv2_d_1200_1302_s_2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[薊馬與粉蝨自動監測裝置與防治決策系統
]]></title><description><![CDATA[臺灣農作物之栽培管理因有害生物種類繁多且週年發生，稍有不慎即造成病蟲之族群激增，嚴重影響農產品產量品質。害蟲綜合管理可以運用可靠的自動監測技術，來掌握害蟲發生動態與數量，再透過精準的分析管理決策系統，做出正確合理的判斷，選用適當資材進行防治。...]]></description><link>https://siplab.wixsite.com/wujl/post/%E8%96%8A%E9%A6%AC%E8%88%87%E7%B2%89%E8%9D%A8%E8%87%AA%E5%8B%95%E7%9B%A3%E6%B8%AC%E8%A3%9D%E7%BD%AE%E8%88%87%E9%98%B2%E6%B2%BB%E6%B1%BA%E7%AD%96%E7%B3%BB%E7%B5%B1</link><guid isPermaLink="false">5b853d5d1c0de9001ec9b79a</guid><pubDate>Tue, 28 Aug 2018 12:20:18 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_549c3b91516642969e86c60cb9d238f7~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[A hybrid motion deblurring strategy using patch based edge restoration and bilateral filter]]></title><description><![CDATA[Motion blur is a common problem in digital photography. In the dim light, a long exposure time is needed to acquire a satisfactory...]]></description><link>https://siplab.wixsite.com/wujl/post/image-deblurring</link><guid isPermaLink="false">5aa8d864d57cd2027f0d784c</guid><pubDate>Wed, 14 Mar 2018 08:08:04 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_f9d90d87338844fe988a5f9f7ef356bd~mv2.png/v1/fit/w_1000,h_888,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[A single image deblurring algorithm for nonuniform motion blur using uniform defocus map estimation]]></title><description><![CDATA[One of the most common artifacts in digital photography is motion blur. When capturing an image under dim light by using a handheld...]]></description><link>https://siplab.wixsite.com/wujl/post/a-single-image-deblurring-algorithm-for-nonuniform-motion-blur-using-uniform-defocus-map-estimation</link><guid isPermaLink="false">5aa8d864d57cd2027f0d784b</guid><pubDate>Wed, 14 Mar 2018 08:08:04 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_a993416915ac45ad870a5a7737e1b146~mv2.jpg/v1/fit/w_928,h_620,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[A fast classification strategy for SVM on the large-scale
high-dimensional datasets]]></title><description><![CDATA[The challenges of the classification for the largescale and high-dimensional datasets are: (1) It requires huge computational burden in...]]></description><link>https://siplab.wixsite.com/wujl/post/a-fast-classification-strategy-for-svm-on-the-large-scale-high-dimensional-datasets</link><guid isPermaLink="false">5aa8d864d57cd2027f0d784a</guid><pubDate>Wed, 14 Mar 2018 08:08:04 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_b54a9c45f0d848bba27125567a04ddf9~mv2.jpg/v1/fit/w_852,h_851,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item><item><title><![CDATA[A hybrid defect detection method for
compact camera lens]]></title><description><![CDATA[Production technology has increased rapidly with the development of industrial technology. Conventional human visual inspection is...]]></description><link>https://siplab.wixsite.com/wujl/post/a-hybrid-defect-detection-method-for-compact-camera-lens</link><guid isPermaLink="false">5aa8d864d57cd2027f0d7849</guid><pubDate>Wed, 14 Mar 2018 08:08:04 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/33750e_654a53a4726846379c62127c8682e2a7~mv2.png/v1/fit/w_894,h_830,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>SIPLab</dc:creator></item></channel></rss>