ONE WEEK GIAN COURSE ON

VISUAL OBJECT RECOGNITION

15th Jan.2018 to 19th Jan. 2018

Due to the rapid development in electronics, communication and hardware technology, there is a high demand for the design of automated intelligent systems in industrial works, medical imaging, defense and biometrics. The performance of such automated intelligent systems depends upon suitable choice of machine learning algorithms. The machine learning process involves object extraction, representation and classification.

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Recognition is a rather broad and quickly moving field

We limit our scope to methods that are already used fairly frequently in the literature and we assume that the reader has basic familiarity with machine learning algorithms for supervised classification, and some background in low-level image processing.

OBJECTIVES

The primary objectives of the course are as follows:

Explore

Exploring the fundamentals of Machine Learning and Computer Vision

Overview

To provide an overview on the types of methods that figure most prominently in object recognition research today, in order to give a survey of the concepts, algorithms, and representations that one might use to build a visual recognition system.

Exposure

Providing an exposure to practical problems and their solutions, through case studies on surveillance and biometrics based live projects in object recognition

Wrap up

We wrap up our coverage of specific objects by outlining example end-to-end systems from recent work, pulling together the key steps on local features and matching.

LECTURE SCHEDULE

Motivation

Problems
Machine Learning concepts

Basics in Classification

NN, Generative Classifier, Linear Classifiers, Non-Linear With Kernels

Features, Object Localization

Local Features, Bag Of Words, Pooling
Viola/Jones, HOG)

Deep Learning

ANN, CNN, LSTM
Current Research Directions

Life-Long Learning

Novelty Detection, Active Learning
Incremental update of classifiers

Who Should Attend

Student at all levels (BTech/BE/ME/MCA/MSc/MTech/PhD)

Faculty from Universities and Technical Institutions

Researchers from Industry

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Speakers

Participation Fees

The participation fees for taking the course is as follows

The participants will be provided with accommodation on payment basis.

UG/PG Students

Rs.1000/-

Research Scholars

Rs.2000/-

Faculty/ Freelancer

Rs.3000/-

Industry Participants

Rs. 5000/-

International Participants

300/- USD

CONTACT DETAILS

Prof. B H SHEKAR.

Department of Studies and Research in Computer Science,
Mangalore University, Mangalagangothri,
Mangalore – 574 199, Karnataka.

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