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33 results

CampusX
POS Tagging | Part of Speech Tagging in NLP | Hidden Markov Models in NLP | Viterbi Algorithm in NLP

Dive into the world of Natural Language Processing (NLP) with this comprehensive guide on Part of Speech (POS) Tagging.

1:01:41
POS Tagging | Part of Speech Tagging in NLP | Hidden Markov Models in NLP | Viterbi Algorithm in NLP

102,072 views

3 years ago

Marcus Sherman
betteridiot: Office Hours! Hidden Markov Models (HMMs) and the Viterbi Algorithm

better idiot office hours! Today's topic: Hidden Markov Models with Python Office Hours is a resource created for the Bioinformatics ...

2:03:38
betteridiot: Office Hours! Hidden Markov Models (HMMs) and the Viterbi Algorithm

127 views

6 years ago

IACR
Side Channel Information Set Decoding using Iterative Chunking

Paper by Norman Lahr, Ruben Niederhagen, Richard Petri, Simona Samardjiska presented at Asiacrypt 2020 See ...

24:39
Side Channel Information Set Decoding using Iterative Chunking

376 views

5 years ago

FOSDEM
Decoding Meteor-M2: QPSK, Viterbi, Reed Solomon and JPEG from IQ coefficients to images, analysis o…

Decoding Meteor-M2: QPSK, Viterbi, Reed Solomon and JPEG from IQ coefficients to images, analysis of digital weather satellite ...

29:58
Decoding Meteor-M2: QPSK, Viterbi, Reed Solomon and JPEG from IQ coefficients to images, analysis o…

827 views

6 years ago

Electrical & Computer Learning Center, ECL Center
Introduction to EECS II Digital Communication Systems - MIT - Lec 07

Lecture 07: Viterbi Decoding Description: This lecture starts with a review of encoding and decoding. The Viterbi algorithm, which ...

49:23
Introduction to EECS II Digital Communication Systems - MIT - Lec 07

10 views

8 months ago

Waltenegus Dargie
Hidden Markov Models (Part III: Uncovering Hidden States): Dr. Waltenegus Dargie (TU Dresden)

In this lecture uncovering the hidden states of a HMM which could have generated a sequence of observations will be discussed.

39:45
Hidden Markov Models (Part III: Uncovering Hidden States): Dr. Waltenegus Dargie (TU Dresden)

108 views

5 years ago

Waltenegus Dargie
Hidden Markov Models (Part II. Likelihood Probability): Dr. Waltenegus Dargie (TU Dresden)

In this lecture the computation of the likelihood probability of a sequence of observations given a Hidden Markov Model will be ...

24:27
Hidden Markov Models (Part II. Likelihood Probability): Dr. Waltenegus Dargie (TU Dresden)

196 views

5 years ago

IACR
Syndrome Decoding Estimator

Paper by Andre Esser, Emanuele Bellini presented at PKC 2022 See https://iacr.org/cryptodb/data/paper.php?pubkey=31701.

26:13
Syndrome Decoding Estimator

523 views

3 years ago

Computational Linguistics @ Illinois
Stack decoding for statistical phrase-based machine translation

This video walks through the stack decoding algorithm for a simple sentence, taken from the Chapter 6 slides of Statistical ...

30:01
Stack decoding for statistical phrase-based machine translation

1,170 views

8 years ago

Tanja Lange: Post-quantum cryptography
Code-based cryptography V - Information-set decoding

This lecture is part of Post-quantum cryptography" part of the MasterMath course "Selected Areas in Cryptology" For details see ...

26:46
Code-based cryptography V - Information-set decoding

1,959 views

4 years ago

NPTEL IIT Guwahati
Lec 23: Hidden Markov Model (HMM)

Machine Learning and Deep Learning - Fundamentals and Applications https://onlinecourses.nptel.ac.in/noc23_ee87/preview ...

1:02:40
Lec 23: Hidden Markov Model (HMM)

8,402 views

2 years ago

IACR
Smaller Decoding Exponents: Ball-Collision Decoding

Talk at crypto 2011. Authors: Daniel J. Bernstein, Tanja Lange, Christiane Peters.

20:53
Smaller Decoding Exponents: Ball-Collision Decoding

325 views

14 years ago

ISCA SynSIG
SPCC 2016 - Simon King - Speech synthesis using HMM

Lecture on HMM speech synthesis offered by Simon King during the Speech Processing Courses in Crete (SPCC) Summer ...

1:50:11
SPCC 2016 - Simon King - Speech synthesis using HMM

1,021 views

5 years ago

nptelhrd
lecture15

Decoder for the re solement code you see you'll get a similar framework like the like the bch code except that there'll be some ...

48:00
lecture15

362 views

10 years ago

FOSDEM
Task Scheduling of Software-Defined Radio Kernels in Heterogeneous Chips: Opportunities and Challen…

Task Scheduling of Software-Defined Radio Kernels in Heterogeneous Chips: Opportunities and Challenges by Augusto Vega At: ...

24:14
Task Scheduling of Software-Defined Radio Kernels in Heterogeneous Chips: Opportunities and Challen…

264 views

5 years ago

nptelhrd
lecture32

Try try to work this out by yourself so this is very important in the turbo decoder okay so we'll use this over and over again and uh ...

1:09:51
lecture32

307 views

10 years ago

Minjoon Seo
Deep Learning for NLP - 06 (KAIST AI605 Spring 2021)

Class website: https://seominjoon.github.io/kaist-ai605/

1:12:17
Deep Learning for NLP - 06 (KAIST AI605 Spring 2021)

305 views

4 years ago

ICIOUMH
Conferencia “Convolutional codes with Network Coding“

El Centro de Investigación Operativa de la UMH (CIO) de Elche acogió el pasado 14 de septiembre esta conferencia del profesor ...

46:12
Conferencia “Convolutional codes with Network Coding“

174 views

8 years ago

LispNYC
Chapter 05: Decision Theory

Presenter: Dr. Saty Raghavachary (Associate Professor of Computer Science at the University of Southern California) Date: ...

1:20:54
Chapter 05: Decision Theory

654 views

4 years ago

nptelhrd
Lecture24

... Go run through It's easy to simulate M of Z It's easy to simulate noise It's easy to well maybe it's easy to simulate the wid decoder ...

51:19
Lecture24

261 views

10 years ago