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CE

Centre for Data Science and Applied Machine Learning

CDSAML

RR Campus cdsaml@pes.edu
20
Publications
Overview
About the research centre
Research Areas
Fields of research and focus
Team
Researchers and team members
Publications
Research publications and papers
Resources
Tools and technologies used

About CDSAML

Centre for Data Science and Applied Machine Learning(CDSAML) at PES University focuses on Image Processing, Computer Vision and Pattern Recognition using technologies from Artificial Intelligence, Machine Learning and Deep learning. Social Media Analytics using technologies from Statistical Machine Learning(SML), Natural Language Processing and Information Visualization. The goal of CDSAML is to build systems and algorithms to extract knowledge, find patterns, generate insights and predictions from diverse data for various applications and visualization. The center conducts survey research, qualitative data collection, and data analysis.

Areas of Research

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Face Recognition
Abnormal Event Detection
Scene understanding, Scene construction
Object Detection and Classification
Video and Text Summarization
Material Characterization

Our Researchers

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D
faculty
Dr. Shylaja S S
Director of CCBD, CDSAML
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D
faculty
Dr. Uma D
Professor
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D
faculty
Dr. Ashwini M Joshi
Associate Professor
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D
faculty
Dr. Sivagamasundari G
Associate Professor
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Research Publications

20

Authors: Kaushik Ravi , Nypunya Devraj, Shylaja S S,

Authors: Nidhi P G, Disha M, Siddharth Soora, Pranav Bookanakere and Uma D.

Authors: Preethi P, Rohit Suresh, Mutasim M, Yashwin S, Sana Suman

Authors: Ashwini Joshi,

Tools & Technologies

Software Tools 5
OpenCV

OpenCV is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products

Natural Language Toolkit

NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum.

Technologies 5
Image Processing Computer Vision Machine Learning Natural Language Processing Data Science