Duration : 15th April 2024 , 10:00 AM – 11:30 AM
Mode : Online
Venue : Programming Lab & Project Lab, 7th Floor, BMS – Block
Participants : 97
Objective : To train and equip the students with foundational knowledge and skills in the field of Optimizing Object Detection Approaches
A guest lecture on the topic “Optimizing Object Detection Approaches” was conducted on 15th April 2024 by Dr.S.Jeba Berlin, Post doctoral researcher from IIIT, Bangalore. Topics covered were SVM, Logistic regression, Harris corner reduction, SIFT features, CNN & RCNN and Deep learning architecture. The following topics were briefly discussed.
- SVM: Support Vector Machines (SVM) uses in various fields like image classification, text classification, and bioinformatics to efficiently classify data points by finding the optimal hyperplane were discussed.
- Harris Corner Reduction: Harris Corner Reduction in detecting key points or corners using the Harris Corner Detector algorithm was explained
- SIFT Features: SIFT (Scale-Invariant Feature Transform) features for matching and recognizing objects across varying scales and orientations by detecting key points, describing their local gradients, and generating a histogram-based representation of their surrounding neighbourhoods were discussed.
- CNN and RCNN: Convolutional Neural Networks (CNN) and Region-Based Convolutional Neural Networks (R-CNN) through a combination of region proposals and CNN feature extraction and Deep Learning Architecture and its modules were explained.
The Guest Lecture on “Optimizing Object Detection Approaches” concluded successfully, achieving its goal of educating and empowering students with knowledge on feature extraction and classification for images. Students actively participated and interacted with the speaker and vote of thanks was given by Dr.M.Latha, AP/IT.
Convenor
Dr. Rajeswari Mukesh, Professor & HOD/IT, SRMIST, Ramapuram.
Co-Convenors
Dr.M. Latha (AP/IT), Dr.K.DAnesh(AP/IT), SRMIST,Ramapuram.
