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2026-10-21, Week 43
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main_email:francis-cm.lau@polyu.edu.hk
Presentation Submission Go to [Presentation]
Work Method
* Looking though a Presentation Sample (click!!) as the target.
Step.1: Submit a slide (select slide number + upload .jpg + description) + Write button (Save)
Step.2: Review a submitted slide with .jpg and description, and listen text to speech function
Step.3: Any time, edit it by selecting the slide hyper link on top a slide + Write button (Save)
*Give it a try right away!!
Paper Number
Paper Title
Keyword
Online Presentation * Submit YouTube URL: Compulsory for online participant!
Slide Number * Upload slide file one by one, Notice: .jpg(O) .JPG(X), click -> slide20.jpg  
* Min. 20 ~ Max. 40 slides!!
Slide Display
Verbal Description
*Must fill up in details as much as you can do!
Save the slide and description

*** You can edit any slide by selecting the Slide number below***
ICACT20240009 Slide.20        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Q&A

ICACT20240009 Slide.19        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Future works

ICACT20240009 Slide.18        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Performance of proposed LSTM-THC decoder

ICACT20240009 Slide.17        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Training LSTM-THC decoder

ICACT20240009 Slide.16        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Performance of proposed LSTM-CHC decoder

ICACT20240009 Slide.15        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Training evolution

ICACT20240009 Slide.14        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Training LSTM-CHC decoder

ICACT20240009 Slide.13        [Big slide for presentation]       Chrome Text-to-Speach Click!!
End-to-end THC decoder based on bi-directional LSTM

ICACT20240009 Slide.12        [Big slide for presentation]       Chrome Text-to-Speach Click!!
CHC decoder based on bi-directional LSTM

ICACT20240009 Slide.11        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Conventional CHC and THC decoders

ICACT20240009 Slide.10        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Turbo Hadamard code

ICACT20240009 Slide.09        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Convolutional Hadamard code

ICACT20240009 Slide.08        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Decoding convolutional code via bi-directional RNN network

ICACT20240009 Slide.07        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Convolutional code

ICACT20240009 Slide.06        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Recurrent neural network (RNN) takes the previous output and hidden states as inputs so that the composite input at time 𝑡 has some historical information about what happens at time T<𝑡

ICACT20240009 Slide.05        [Big slide for presentation]       Chrome Text-to-Speach Click!!
The communication model is similar

ICACT20240009 Slide.04        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Characteristics of deep learning model include the following

ICACT20240009 Slide.03        [Big slide for presentation]       Chrome Text-to-Speach Click!!
The goal of deep learning is to learn from data

ICACT20240009 Slide.02        [Big slide for presentation]       Chrome Text-to-Speach Click!!
Deep learning has been applied in our daily lives. Examples are object classification, object detection and language translation

ICACT20240009 Slide.01        [Big slide for presentation]       Chrome Text-to-Speach Click!!
These are the contents of the presentation

ICACT20240009 Slide.00        [Big slide for presentation]       Chrome Text-to-Speach Click!!
I am Francis Lau, the presenter of this paper