ai flower vector的問題,透過圖書和論文來找解法和答案更準確安心。 我們找到下列包括價格和評價等資訊懶人包
ai flower vector的問題,我們搜遍了碩博士論文和台灣出版的書籍,推薦寫的 Soft Computing and Signal Processing: Proceedings of 4th ICSCSP 2021 可以從中找到所需的評價。
另外網站Flower Images | Free Vectors, Stock Photos & PSD - Freepik也說明:
國立臺灣科技大學 應用科技研究所 鄭智嘉所指導 Ashenafi Zeleke Melaku的 自組裝超分子聚合物輔助二維奈米材料的可擴展液相剝離和分散 (2021),提出ai flower vector關鍵因素是什麼,來自於。
而第二篇論文國立臺灣師範大學 圖文傳播學系碩士在職專班 周遵儒所指導 林昭伶的 花語之色彩意象應用於色彩建議與分析 (2021),提出因為有 色彩學、色彩心理學、色彩意象、色彩建議、人工智慧、深度學習的重點而找出了 ai flower vector的解答。
最後網站Flower Vector Free | AI, SVG and EPS則補充:Free Flower vector download in AI, SVG, EPS and CDR. Browse our Flower images, graphics, and designs from +79.322 free vectors graphics.
Soft Computing and Signal Processing: Proceedings of 4th ICSCSP 2021
為了解決ai flower vector 的問題,作者 這樣論述:
Data Preprocessing and finding optimal value of K for KNN Model.- Prediction of Cardiac Diseases using Machine Learning Algorithms.- A Comprehensive Approach to Misinformation Analysis and Detection of Low-Credibility News.- Evaluation of Machine Learning Algorithms for Electroencephalography based
Epileptic Seizure State Recognition.- Lung Disease Detection and Classification from Chest X-Ray Images using Adaptive Segmentation and Deep Learning.- A Quantitative analysis for Breast Cancer prediction using Artificial Neural Network and Support Vector Machine.- Tracking Misleading News of COVID-
19 within Social Media.- Energy aware Multi-chain PEGASIS in WSN: A Q-Learning Approach.- TEXTLYTIC: Automatic Project Report Summarization using NLP Techniques.- Management of Digital Evidence for Cybercrime Investigation- A Review.- Realtime Human Pose Detection and Recognition using Mediapipe.- C
harge the Missing Data with Synthesized Data by using SN-Sync technique.- Discovery of Popular Languages from GitHub Repository: A Data Mining.- Performance Analysis of Flower Pollination Algorithms using Statistical Methods: An Overview.- Counterfactual causal analysis on structured data.- Crime An
alysis Using Machine Learning.- Multi-Model Neural Style Transfer for Audio and Image (MMNST).- Feature Extraction from Radiographic Skin Cancer Data using LRCS.- Shared Filtering-Based Advice Of Online Group Voting.- Mining Challenger From Bulk Preprocessing Datasets.- Prioritized Load Balancer for
minimization of VM and Data Transfer Cost in Cloud Computing.- Smart Underground Drainage Management System using Internet of Things.- Iot Based System For Health Monitoring Of Arrhythmia Patients Using Machine Learning Classification Techniques.- EHR-Sec: A Blockchain based Security System for Ele
ctronic Health.- End to End Speaker Verication For Short Utterances.- A Comprehensive Analysis on Multi-class Imbalanced Bigdata Classification.- Efficient Recommender System for Kid’s Hobby using Machine Learning.- Programming Associative Memories.- Novel Associative Memories based on Spherical Sep
erability.- An Intelligent Fog-IoT based Disease Diagnosis Healthcare System.- Pre-processing of linguistic divergence in English- Marathi language pair in Machine Translation.- Deep Learning Approach for Image Based Plant Species Classification.- Inventory, Storage and Routing Optimization with Hom
ogeneous Fleet in the Secondary Distribution Network Using a Hybrid VRP, Clustering and MIP Approach.- Evaluation and Comparison of various static and dynamic load balancing strategies used in cloud computing.- Dielectric Resonator Antenna with Hollow Cylinder for Wide Bandwidth.- Recent Techniques
in Image Retrieval: A Comprehensive Survey.- Medical Image Fusion Based On Energy Attribute and PA-PCNN in NSST Domain.- Electrical Shift and Linear Trend artifacts removal from single channel EEG using SWT-GSTV model.- Forecasting Hourly Electrical Energy output of a Power plant using parametric mo
dels.- Cataract detection using Deep Convolutional Neural Networks.- Comparative Analysis of Body Biasing Techniques for Digital Integrated Circuits.- Optical Mark Recognition with Facial Recognition System.- Evaluation of Antenna Control System for Tracking Remote Sensing Satellites.- Face Recognit
ion using Cascading of HOG and LBP Feature Extraction.- Design of wideband patch Antenna using metamaterial and Dielectric resonator Structures.- Call Admission Control for Interactive Multimedia Applications in 4G Networks.- AI-based Pro-Mode in Smartphone Photography.- A ML-Based Model to Quantify
Ambient Air Pollutant.- Multimodal biometric system using Undecimated Dual-Tree Complex Wavelet Transform.- Design of Modified Dual - Coupled Linear Congruential Generator Method Architecture for Pseudorandom Bit Generation.- Performance Analysis of PAPR and BER in FBMC-OQAM With Low-complexity Usi
ng Modified Fast Convolution.- Sign Language Recognition using Convolution Neural Network.- Key Bas
自組裝超分子聚合物輔助二維奈米材料的可擴展液相剝離和分散
為了解決ai flower vector 的問題,作者Ashenafi Zeleke Melaku 這樣論述:
近期,二維 (2D) 奈米材料在許多應用領域中展現出十足的潛力,如石墨烯、過渡金屬二硫屬化物 (TMDCs)、六方氮化硼 (h-BN) 等,已應用於各種光電元件、傳感器、電容器、太陽能電池等方面。此等材料雖只有單顆或數顆原子之厚,卻擁有在塊材型態不具備的優越特性,使其在未來廣泛的科技研究中展現出色前景。然而,材料性能固然出色,工業級大量生產高質量的二維奈米材料卻非易事,而液相脫層程序正是合適的因應之道,透過界面活性劑與溶劑的搭配,可以簡單、環保的方式有效地大規模產生薄層二維材料。在本文研究中,我們分別在石墨與二硫化鉬(MoS2)兩系統中加入超分子聚合物作為界面活性劑,經由超音波震盪的處理,將
兩材料由三維(3D)大型分子轉為二維形式並大量生產。在研究的第一部分,利用添加腺嘌呤功能化的生物可降解低聚物(3A-PCL),將塊狀結晶的石墨脫層為具導電性、良好物理特性且高度有序結構的石墨烯奈米片,經檢驗後可證明,因3A-PCL對石墨表面具有高親和性,可於其表面自行組裝為層狀奈米結構,在有機溶劑裡脫層並形成穩定懸浮的石墨烯奈米片。而在移除溶劑後,此複合材料在黏性與彈性狀態間顯示出持久的熱可逆相變行為,並可透過調整複合材料內的聚合物比例,進而調控脫層石墨烯的厚度。此石墨烯複合材料最大的特色在於電阻率低,測得之數值為1.5 ± 0.7 mΩ·cm,比原始石墨烯低一個數量級以上。綜合第一實驗系統的
研究,選用液相脫層程序製備多功能超分子與石墨的奈米複合材料,因其生產過程簡單,製成之材料具有良好的物理特性與導電性,適合在導電元件領域發展應用。本研究的第二部分,我們以鄰二氯苯(ODCB)為溶劑,腺嘌呤功能化聚丙二醇(A-PPG)為界面活性劑,設計一種能將石墨脫層為厚度可控之高質量石墨烯的實驗系統。首先我們先在溶劑ODCB中,把天然石墨剝離為數層有序的脫層石墨(EG)奈米片,此視為一次脫層;而在二次脫層中,在EG溶液中加入A-PPG,此時具氫鍵官能基的腺嘌呤發揮關鍵作用,使A-PPG能在石墨烯奈米片表面自行組裝為長而有序的奈米結構,進而增加EG在ODCB中的長期分散穩定性,且透過調整複合材料中
A-PPG的含量,可製備出具特定結構特徵的石墨烯奈米片。此以超分子聚合物作非共價官能化的石墨烯表現非凡,經由簡單、有效的一次及二次脫層,可自由調控石墨烯的所需厚度,在各項潛在應用中發揮作用。最後一實驗系統,則是以水為溶劑,胞嘧啶功能化聚丙二醇(Cy-PPG)為界面活性劑,搭配二次脫層程序,將MoS2剝離為超薄層的奈米片。首先,利用水相環境將原始的MoS2初步分散為數層的奈米片,接著於二次脫層期間加入Cy-PPG,與數層MoS2的水溶液進行一小時以上的超音波震盪,此過程中,自組裝為有序層狀奈米結構的Cy-PPG會因強物理作用力而吸附在奈米片的表面,並形成可調節的超薄層MoS2,而透過仔細調整Cy
-PPG的用量,可以大幅改善MoS2在水溶液的長期穩定分散性,從而保持其固有的特性,最後利用光譜及顯微鏡分析脫層奈米片的形貌與物理性質,證明MoS2奈米片表面確實有Cy-PPG的存在,而在導電率測試中,測得之數值則較原始MoS2高出127 µS/cm。綜觀以上,此實驗系統能夠有效以環保方法生產超薄層MoS2奈米片,對於講求材料精準的研究領域至關重要。
花語之色彩意象應用於色彩建議與分析
為了解決ai flower vector 的問題,作者林昭伶 這樣論述:
本研究所側重分析的焦點以日本學者小林重順建立色彩意象座標(Color Image Scale)與色彩意象詞彙資料庫(Color Image Word Database),讓情緒與色彩或色彩組合標準化、數值化,以奠定學理討論基礎,其利用語意差異法度量色彩及意象的關聯,與日本色彩與設計研究所(Nippon Color and Design Research Institute, NCD)合作開發色彩意象座標。透過自然語言處理(Natural Language Processing, NLP)技術將一般口語化的表達轉換至專業的一個或多個設計參數的辨識,用於人工智慧(Artificial Intel
ligence, AI)深度學習(Deep Learning)訓練出符合大數據內容呈現趨勢優化的色彩建議的方法,提出具體建議。 透過設計3組實驗「多意象色彩調和演算法」、「色彩意象抽取演算法」、「花卉圖片重點色彩擷取」,進行提取3色色彩組合當作已知色,實作於「色彩建議演算法」輸出建議色,利用網路問卷調查分析滿意度,結果顯示色彩建議後的5色色彩組合的滿意度平均數都比4色色彩組合高。本研究的主題花語之色彩意象應用於色彩建議後的4色、5色色彩組合的滿意度平均數均達3分以上具有正面的評價。另外,本研究觀察審美度方程式M=O/C,花卉圖片重點色彩應用於色彩建議後的4色、5色色彩組合,都有100%符
合M>0.5,發現應是花的顏色色相大多較為相近,產生對應到的數值不會差太大的現象,在曼賽爾色彩系統中如果O與C的落差不夠大,計算得到的數據就不會差太大,進而發現當色彩色相都較為相近時只採用審美度來進行評量色彩調和度是不夠的。 花語被加以利用於色彩意象的表現,輔助設計半自動化色彩建議方法,產生具有代表性或獨特性的色票,未來得以應用於印刷與設計產業中,解決一般非專業人員色彩運用能力不足的困境。COVID-19疫情觸動數位轉型契機,迫切需要大量的資訊傳遞、搜尋與雲端儲存及大數據的使用。科技的進步讓科技推動模式逐漸由技術轉為需求導向(陳聖智,2021),色彩建議方法的效能與創新應用的可行性,導入
人工智慧概念,無須透過漫長歲月經驗累積養成,輔助更多有設計需求但能力不足的人,即時性設計因應少量多樣、個人化、個性化的趨勢設計潮流,亦是本研究主要課題以供後續相關研究與應用之參考。
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