Capacitive stylus的問題,透過圖書和論文來找解法和答案更準確安心。 我們找到下列懶人包和總整理

國立成功大學 電機工程學系 林志隆所指導 朱庭慶的 適用於初期失智檢測之互動認知系統與機器學習空間記憶能力辨識演算法開發 (2020),提出Capacitive stylus關鍵因素是什麼,來自於電容式觸控面板、適應性卡爾曼濾波器、嵌入式系統、克羅斯積木、認知檢測、模糊邏輯系統、支持向量機、特徵選擇、階層式分群法。

而第二篇論文國立中央大學 光電科學與工程學系 孫文信所指導 林哲玄的 手機上隱藏式指紋辨識設計 (2020),提出因為有 指紋辨識、光學設計、全內反射、準直器的重點而找出了 Capacitive stylus的解答。

接下來讓我們看這些論文和書籍都說些什麼吧:

除了Capacitive stylus,大家也想知道這些:

Capacitive stylus進入發燒排行的影片

Greetings. My name is themblan, and I am a boy-gamer.

Super Mario Maker 2 is finally here! Recently, I decided to really concentrate on saving money, but I had to get this game. I have been waiting a long time for it.

I am a little apprehensive about making levels, because it was so fun making levels on the original game for Wii U with the stylus. You can use a capacitive stylus, but it is not as accurate as using a stylus on the Wii U Gamepad's resistive touchscreen.

For this first episode, I decided to just play the game for now, and make levels later.

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Super Mario Maker 2 was developed by Nintendo EPD and published by Nintendo. It is available exclusively on Nintendo Switch.

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Thank you for watching, and have a great day.

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The song in my intro and outro was done by Hyper Potions, and it is called Time Trials. You can check out the full song here: https://youtu.be/mnfNWe-HHsI.

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My Socials:

Twitter: http://www.twitter.com/themblan1
Instagram: https://www.instagram.com/themblan1

適用於初期失智檢測之互動認知系統與機器學習空間記憶能力辨識演算法開發

為了解決Capacitive stylus的問題,作者朱庭慶 這樣論述:

摘要 iAbstract iiiAcknowledgements viContents viiList of figures ixList of tables xiiCHAPTER 1 Introduction 11.1. Background 11.2. Motivation 31.3. Dissertation organization 7CHAPTER 2 Touch experience enhancement algorithm based on adaptive kalman filter for touchscreen panel 92.1. Introduction

92.2. Proposed touchscreen panel configuration 112.3. Adaptive Kalman filter 122.4. Experiment results 152.5. Summary 18CHAPTER 3 Evaluation of novel cognitive assessment system for testing visual memory of the elderly 233.1. Introduction 233.2. Corsi block tapping task on interactive cognitive syst

em 263.3. Experimental results 293.4. Summary 33CHAPTER 4 Machine learning-based classification algorithm for degree of difficulty in corsi block tapping task 434.1. Introduction 434.2. Feature analysis method for path level 454.3. Experiment results 514.4. Summary 53CHAPTER Conclusion 655.1. Concl

usion 655.2. Future work 67Reference 68Appendix 74A.1. Supporting documents 74A.2. Biography 75A.3. Publication list 76

手機上隱藏式指紋辨識設計

為了解決Capacitive stylus的問題,作者林哲玄 這樣論述:

本論文針對現今主流的兩種面板手機提出隱藏於屏幕下的指紋辨識光學設計,一個為適用於Liquid Crystal Display (LCD)屏幕下的指紋辨識,另一個為適用於Organic Light-Emitting Diode (OLED)屏幕下的超薄型指紋辨識。LCD屏幕本身不具透明特性,要讓其實現屏幕下指紋辨識的難度較高,因此我們提出一個設計方法將屏幕表面的保護玻璃(Cover Glass)作為導光板,當指紋按壓在玻璃表面時,指紋的脊會破壞導光板的全反射特性紀錄下指紋的紋路。另外,我們在保護玻璃的出入瞳處設計一個反射斜面,此斜面具有斜向投影放大與縮小的功能,讓外觀設計可以達到窄邊框(Bez

el Less)需求,使屏佔比可達98%。最後將設計實現在LCD屏幕手機上並取得高對比度的指紋影像。在OLED屏幕下超薄型指紋辨識設計部分,我們提出一個利用光阻堆疊的方式來製作準直器取代傳統Through Silicon Via (TSV)的方式可以降低製作成本。另外,模組整體厚度小於0.6 mm的設計使其可以被放到屏幕與手機中框之間,讓電池的體積不在受到指紋辨識模組影響。最後,我們將此模組實作並組裝到OLED屏幕與手機中框內,利用OLED屏幕發光取得良好對比度的指紋影像。