Bedform Parameterization and Object Detection from Sonar Data- Application of Finger Print Algorithms

2012 ◽  
Author(s):  
Arthur C. Trembanis ◽  
Larry Mayer ◽  
Jonathan Beaudoin
Keyword(s):  
Object Detection ◽  
Finger Print ◽  
Data Application

Short-Form Application of the Screening Test of Spanish Grammar and the Northwestern Syntax Screening Test to Latino Children

1978 ◽  
Vol 9 (4) ◽  
pp. 220-235
Author(s):  
David L. Ratusnik ◽  
Carol Melnick Ratusnik ◽  
Karen Sattinger
Keyword(s):  
New York ◽  
Case Studies ◽  
Metropolitan Area ◽  
Screening Test ◽  
Normative Data ◽  
Short Form ◽  
Latino Children ◽  
Data Application ◽  
York Metropolitan Area ◽  
Multiple Regression Technique

Short-form versions of the Screening Test of Spanish Grammar (Toronto, 1973) and the Northwestern Syntax Screening Test (Lee, 1971) were devised for use with bilingual Latino children while preserving the original normative data. Application of a multiple regression technique to data collected on 60 lower social status Latino children (four years and six months to seven years and one month) from Spanish Harlem and Yonkers, New York, yielded a small but powerful set of predictor items from the Spanish and English tests. Clinicians may make rapid and accurate predictions of STSG or NSST total screening scores from administration of substantially shortened versions of the instruments. Case studies of Latino children from Chicago and Miami serve to cross-validate the procedure outside the New York metropolitan area.

ANALISIS PELAYANAN PUBLIK PADA KANTOR CAMAT PASEMAH AIR KERUH KABUPATEN EMPAT LAWANG

2018 ◽  
Vol 7 (1) ◽  
pp. 33
Author(s):  
Anwar Hamid ◽  
Muhammad Zimi
Keyword(s):  
Finger Print

Penelitian dilakukan pada Kantor Camat Pasemah Air Keruh Kabupaten Empat Lawang. Dengan tujuan untuk mengetahui proses pelayanan publik pada Kantor Camat, penelitian menggunakan data primer yaitu data yang diperoleh langsung dari tanggapan masyarakat yang ada dilingkungan kantor Kantor Camat Pasemah Air Keruh Kabupaten Empat Lawang yang pernah menggunakan pelayanan. Di samping itu penulis juga menggunakan data sekunder yaitu informasi yang diperoleh dari laporan berbagai sumber yang ada, menggunakan metode penelitian kualitatif dengan analisis deskriptif kualitatif. Hasilnya menunjukkan bahwa pelayanan publik di Kantor Camat Pasemah Air Keruh Kabupaten Empat Lawang yaitu cukup baik. Hal ini dapat dibuktikan dengan adanya hasil informan tentang aspek-aspek keterbukaan, keadilan, keamanan dan kejelasan, dan efesien pelayanan semua menunjukkan masih adanya permasalahan yang mengakibatkan rendahnya kualitas pelayanan Kantor Camat Pasemah Air Keruh Kabupaten Empat Lawang. Adapun rekomendasi untuk pegawai Kecamatan Pasemah Air Keruh diharapkan lebih disiplin  dalam melakukan pelayanan kepada masyarakat, tidak pernah ada kata terlambat, dan selalu ada ditempat pada saat jam kerja, serta menggunakan absen finger print kepada seluruh aparatur Kantor Camat Pasemah Air Keruh, Melayani masyarakat supaya lebih terbuka baik prosedur ataupun biaya pelayanan, perlu diadakan pendidikan dan pelatihan (Diklat) bagi aparatur untuk meningkatkan kinerja pelayanan di Kecamatan Pasemah Air Keruh. Aparatur Kecamatan Pasemah Air Keruh dalam memberikan pelayanan agar lebih ikhlas dan sadar bahwa sebagai abdi masyarakat, sudah pantasnya memberikan pelayanan prima kepada masyarakat Kecamatan Pasemah Air Keruh.

Automatic accounting of Baikal diatomic algae: approaches and prospects

2019 ◽  
pp. 295-299
Author(s):  
Кonstantin А. Elshin ◽  
Еlena I. Molchanova ◽  
Мarina V. Usoltseva ◽  
Yelena V. Likhoshway
Keyword(s):  
Object Detection ◽  
Loss Function ◽  
Classification Accuracy ◽  
Diatom Species ◽  
Bounding Box ◽  
Synedra Acus ◽  
And Training

Using the TensorFlow Object Detection API, an approach to identifying and registering Baikal diatom species Synedra acus subsp. radians has been tested. As a result, a set of images was formed and training was conducted. It is shown that аfter 15000 training iterations, the total value of the loss function was obtained equal to 0,04. At the same time, the classification accuracy is equal to 95%, and the accuracy of construction of the bounding box is also equal to 95%.

Object Detection in Cluttered Range Images Using Edgel Geometry

2010 ◽  
Vol 130 (9) ◽  
pp. 1572-1580
Author(s):  
Dipankar Das ◽  
Yoshinori Kobayashi ◽  
Yoshinori Kuno
Keyword(s):  
Object Detection ◽  
Range Images

Object Detection Using an Ideal Observer Model

2020 ◽  
Vol 2020 (16) ◽  
pp. 41-1-41-7
Author(s):  
Orit Skorka ◽  
Paul J. Kane
Keyword(s):  
Object Detection ◽  
Matched Filter ◽  
Image Sensors ◽  
Ideal Observer ◽  
Noise Power ◽  
Relative Evaluation ◽  
Detection And Identification ◽  
Cross Correlation Analysis ◽  
Observer Model ◽  
The Ideal

Many of the metrics developed for informational imaging are useful in automotive imaging, since many of the tasks – for example, object detection and identification – are similar. This work discusses sensor characterization parameters for the Ideal Observer SNR model, and elaborates on the noise power spectrum. It presents cross-correlation analysis results for matched-filter detection of a tribar pattern in sets of resolution target images that were captured with three image sensors over a range of illumination levels. Lastly, the work compares the crosscorrelation data to predictions made by the Ideal Observer Model and demonstrates good agreement between the two methods on relative evaluation of detection capabilities.

ON METHODS OF OBJECT DETECTION IN VIDEO STREAMS

2017 ◽  
Vol 2 (1) ◽  
pp. 80-87
Author(s):  
Puyda V. ◽  
◽  
Stoian. A.
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Open Source ◽  
Feature Detection ◽  
Video Stream ◽  
Object Identification ◽  
Vision Systems ◽  
Modern Computer ◽  
Computer Vision Systems ◽  
Open Source Hardware

Detecting objects in a video stream is a typical problem in modern computer vision systems that are used in multiple areas. Object detection can be done on both static images and on frames of a video stream. Essentially, object detection means finding color and intensity non-uniformities which can be treated as physical objects. Beside that, the operations of finding coordinates, size and other characteristics of these non-uniformities that can be used to solve other computer vision related problems like object identification can be executed. In this paper, we study three algorithms which can be used to detect objects of different nature and are based on different approaches: detection of color non-uniformities, frame difference and feature detection. As the input data, we use a video stream which is obtained from a video camera or from an mp4 video file. Simulations and testing of the algoritms were done on a universal computer based on an open-source hardware, built on the Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC processor with frequency 1,5GHz. The software was created in Visual Studio 2019 using OpenCV 4 on Windows 10 and on a universal computer operated under Linux (Raspbian Buster OS) for an open-source hardware. In the paper, the methods under consideration are compared. The results of the paper can be used in research and development of modern computer vision systems used for different purposes. Keywords: object detection, feature points, keypoints, ORB detector, computer vision, motion detection, HSV model color

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