#adaboost

[sobber-full]

فراقِ یار کی بارش، ملال کا موسم

ہمارے شہر میں اترا کمال کا موسم

وہ اک دعا میری، جو نامراد لوٹ آئی

زباں سے روٹھ گیا پھر سوال کا موسم

بہت دنوں سے میرے نیم وا دریچوں میں

ٹھہر گیا ہے تمہارے خیال کا موسم

جو بے یقیں ہو بہاریں اجڑ بھی سکتی ہیں

تو آ کے دیکھ لے میرے زوال کا موسم

محبتیں بھی تیری دھوپ چھاؤں جیسی ہیں

کبھی یہ ہجر، کبھی یہ وصال کا موسم

کوئ ملا ہی نہیں جس کو سونپتے محسنؔ

ہم اپنے خواب کی خوشبو، خیال کا موسم

[assignmentoc]

View this post on Instagram

A post shared by Assignment On Click (@assignmentonclick)

[ijtsrd]

Face Recognition Based Automated Student Attendance System

by Ms. Pranitha Prabhakar | Mr. Kathireshan "Face Recognition Based Automated Student Attendance System"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020,

URL: https://www.ijtsrd.com/papers/ijtsrd38083.pdf

Paper URL : https://www.ijtsrd.com/computer-science/other/38083/face-recognition-based-automated-student-attendance-system/ms-pranitha-prabhakar

peerreviewedinternationaljournal, callforpaperinugcapprovedjournals, paperpublicationforstudent

Face recognition system is very beneficial in real time applications, concentrated in security control systems. Face Detection and Recognition is a vital area in the province of validation. In this project, the Open CV based face recognition strategy has been proposed. This model integrates a camera that captures an input image, an algorithm Haar Cascade Algorithm for detecting face from an input image, identifying the face and marking the attendance in an excel sheet. The proposed system implements features such as detection of faces, extraction of the features, exposure of extracted features, analysis of students attendance, and monthly attendance report generation. Faces are recognized using advanced LBP using the database that contains images of students and is used to identify students using the captured image. Better precision is accomplished in results and the system takes into account the changes that occurs in the face over some time. 

[bigdatacourse]

Machine Learning: Random Forest, Adaboost & Decision Tree https://morioh.com/p/4da3e3122f74?f=5c22e47440738156a7078a19 #morioh #machinelearning #artificialintelligence #randomforest #adaboost #python

[pythonfan-blog]

Machine Learning: Random Forest, Adaboost & Decision Tree https://morioh.com/p/4da3e3122f74?f=5c22e47440738156a7078a19 #morioh #machinelearning #artificialintelligence #randomforest #adaboost #python

[sakshimohitedf]

What is AdaBoost Algorithm - Model, Prediction, Data Preparation - DataFlair

What is AdaBoost, AdaBoost Algorithm Model, Ada Boosting Ensemble, Making Predictions & Data Preparation for AdaBoost, AdaBoost Example, adaptive boosting

[pantechsolution]

View this post on Instagram

“Handwritten recognition using Matlab” Visit pantechsolutions.met #ocr #handwritten #matlab #adaboost #imageprocessing #algorithm https://www.instagram.com/p/B6fZr1cFuJZ/?igshid=x73lkkc3z8xo

[ijtsrd]

Smart Assistant for Blind Humans using Rashberry PI

by Abish Raj. M. S | Manoj Kumar. A. S | Murali. V" Smart Assistant for Blind Humans using Rashberry PI" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, 

URL: http://www.ijtsrd.com/papers/ijtsrd11498.pdf 

Direct URL: http://www.ijtsrd.com/computer-science/embedded-system/11498/ smart-assistant-for-blind-humans-using-rashberry-pi/abish-raj-m-s

best international journal, call for paper papers conference, indexed journal

An OCR (Optical Character Recognition) system which is a branch of computer vision and in turn a sub-class of Artificial Intelligence. Optical character recognition is the translation of optically scanned bitmaps of printed or hand-written text into audio output by using of Raspberry pi. OCRs developed for many world languages are already under efficient use. This method extracts moving object region by a mixture-of-Gaussians-based background subtraction method. A text localization and recognition are conducted to acquire text information. To automatically localize the text regions from the object, a text localization and Tesseract algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Adaboost model. Text characters in the localized text regions are then binaries and recognized by off-the-shelf optical character recognition software. The recognized text codes are output to blind users in speech. Performance of the proposed text localization algorithm. As the recognition process is completed, the character codes in the text file are processed using Raspberry pi device on which recognize character using Tesseract algorithm and python programming, the audio output is listed.