Material featured on this site may be reproduced free of charge in any format or media without requiring specific permission. This is subject to the material being reproduced accurately and not being used in a derogatory manner or in a misleading context.
IIST shall respect and protect the privacy of individual users of its website. Individually identifiable information of the user of the website shall not be willfully disclosed to any third party by IIST without first receiving the user’s permission.
IIST, however, may disclose personal or confidential information about a user if required to do so under the following circumstances:
By accessing this website, you agree that IIST will not be liable for any direct or indirect loss arising from the use of the information and the material contained in this website
Though all efforts have been made to ensure the accuracy and correctness of the content of this website, the same should not be construed as a statement of law or used for any legal purposes. In case of any ambiguity or doubt, users are advised to verify/check with IIST and/or other source(s), and to obtain appropriate professional advice.
Introduction: Representing text, Sounds and Images text, speech, image, and video. Signal processing for feature extraction: for Text (BoW), Speech (LPC, Mel-frequency Capstral coefficients, STFT and Wavelet features), Images (HoG, BoVW, FV), Videos (BoVW).
Introduction and Background of state-of-art sensing and measurement techniques. Contactless potentiometer (resistance-capacitance scheme) – Methodology,Interface Circuits, Overview of Flight Instrumentation. Analog Electronic Blocks, CMRR Analysis (Non-ideal opamps) of an Instrumentation Amplifier, Linearization circuits for single-element wheatstone bridges (application to strain gauge), Direct Digital Converter for Strain gauges, Signal conditioning for Remote-connected sensor elements.
Description: Deep learning methods are now prevalent in the area of machine learning, and are now used invariably in many research areas. In recent years it received significant media attention as well. The influx of research articles in this area demonstrates that these methods are remarkably successful at a diverse range of tasks. Namely self driving cars, new kinds of video games, AI, Automation, object detection and recognition, surveillance tracking etc.
PR overview-Feature extraction-Statistical Pattern Recognition-Supervised Learning-Parametric methods-Non parametric methods; ML estimation-Bayes estimation-k NN approaches. Dimensionality reduction, data normalization. Regression, and time series analysis. Linear discriminat functions. Fishers linear discriminant, linear perceptron and Neural Networks. Kernel methods and Support vector machine. Unsupervised learning and clustering. K-means and hierarchical clustering. Ensemble/ Adaboost classifier, Soft computing paradigms for classification and clustering.
Select a date to view events.