Real-time cloud detection in high resolution images using Maximum Response Filter and Principle Component Analysis

2016 ◽  
Author(s):  
Yihua Tan ◽  
Ji Qi ◽  
Feifei Ren
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Principle Component Analysis ◽  
Component Analysis ◽  
Maximum Response ◽  
Cloud Detection ◽  
Principle Component ◽  
High Resolution Images

scholarly journals Perancangan dan Pengembangan Sistem Absensi Realtime Melalui Metode Pengenalan Wajah

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
I Nyoman Tri Anindia Putra
Keyword(s):  
Real Time ◽  
Principle Component Analysis ◽  
Component Analysis ◽  
Principle Component

Perancangan suatu aplikasi ataupun sistem pengenalan wajah yang baik sangat dibutuhkan dalam mengidentifikasi personal berdasarkan pengenalan wajah yang bisa dimanfaatkan kedalam sebuah sistem keamanan elektronik atau sistem absensi. Berdasarkan beberapa metode yang telah diteliti penulis ingin merancang dan mengembangkan sistem absensi melalui  salah satu metode pengenalan wajah yang memiliki akurasi cukup baik berdasarkan beberapa penelitian sebelumnya, PCA (Principle Component Analysis) atau sering disebut dengan Eigenfaces ini merupakan metode yang multifungsi digunakan, karena Eigenfaces memilki banyak fungsi khususnya dalam pengenalan wajah seperti dapat melakukan prediksi, penghapusan redundansi, kompresi data, reduksi dimensi, sampai pada ekstraksi Ciri  (Marti, 2009) sehingga penulis menggunakan metode eigenfaces sebagai metode yang akan digunakan dalam pengembangan sistem absensi realtime dalam pengenalan wajah tersebut dengan menambahkan metode pada pendeteksian wajah sehingga wajah dapat dideteksi secara realtime. Tujuan dari penulisan tugas akhir ini yaitu dapat mengembangkan dan mengimplemetasikan metode pengenalan wajah Eigenfaces atau PCA kedalam sistem absensi menggunakan deteksi wajah dan melakukan absen dengan menekan tombol absen secara real time serta mengintegerasikan sistem absensi dengan database. Sesuai dengan hasil pengujiannya dapat disimpulkan Sistem absensi yang telah dibuat mampu melakukan proses absensi kepada user secara realtime dengan mendeteksi wajah user melalui metode pengenalan wajah yaitu PCA(Priciple Component Analysis) dengan tingkat akurasi sebesar 90% melalui pengujian secara fungsional akan tetapi Akurasi pada sistem absensi melalui metode pengenalan wajah ini akan semakin buruk jika pencahayaan kurang atau lebih.

Electrical Probing and Surface Imaging of Deep Sub-Micron Integrated Circuits

1999 ◽  
Author(s):  
Kenneth Krieg ◽  
Richard Qi ◽  
Douglas Thomson ◽  
Greg Bridges
Keyword(s):  
High Resolution ◽  
Integrated Circuits ◽  
Real Time ◽  
High Speed ◽  
Time Signal ◽  
Surface Imaging ◽  
Atomic Force ◽  
Submicron Structures ◽  
High Resolution Images ◽  
Capacitive Loading

Abstract A contact probing system for surface imaging and real-time signal measurement of deep sub-micron integrated circuits is discussed. The probe fits on a standard probe-station and utilizes a conductive atomic force microscope tip to rapidly measure the surface topography and acquire real-time highfrequency signals from features as small as 0.18 micron. The micromachined probe structure minimizes parasitic coupling and the probe achieves a bandwidth greater than 3 GHz, with a capacitive loading of less than 120 fF. High-resolution images of submicron structures and waveforms acquired from high-speed devices are presented.

ANALYSIS OF VOICE CUES IN RECOGNITION OF SARCASM

2019 ◽  
Vol 12 ◽  
Author(s):  
Basavaraj N Hiremath ◽  
Malini M Patilb
Keyword(s):  
Feature Extraction ◽  
Computer Program ◽  
Principle Component Analysis ◽  
Voice Recognition ◽  
Component Analysis ◽  
Recognition System ◽  
Principle Component ◽  
Whole Process ◽  
The Voice

The voice recognition system is about cognizing the signals, by feature extraction and identification of related parameters. The whole process is referred to as voice analytics. The paper aims at analysing and synthesizing the phonetics of voice using a computer program called “PRAAT”. The work carried out in the paper also supports the analysis of voice segmentation labelling, analyse the unique features of voice cues, understanding physics of voice, further the process is carried out to recognize sarcasm. Different unique features identified in the work are, intensity, pitch, formants related to read, speak, interactive and declarative sentences by using principle component analysis.

Four challenges for cognitive neuroscience and the cortico-hippocampal division of memory

2003 ◽  
Vol 26 (6) ◽  
pp. 681-682
Author(s):  
Harry Howard
Keyword(s):  
Independent Component Analysis ◽  
Recent Work ◽  
Cognitive Neuroscience ◽  
Principle Component Analysis ◽  
Pattern Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Principle Component ◽  
Complementary Methods ◽  
Current State

Jackendoff's criticisms of the current state of theorization in cognitive neuroscience are defused by recent work on the computational complementarity of the hippocampus and neocortex. Such considerations lead to a grounding of Jackendoff's processing model in the complementary methods of pattern analysis effected by independent component analysis (ICA) and principle component analysis (PCA).

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