let¡¯s look at what i have talked about.
well, that brings me to the end of my presentation. this last slide is a brief summary of what i have talked about.
before i stop/finish, let me just say...
to close my speech, i' 11 show you the last slide.
now i'd like to summarize my talk.
to summarize, i have talked about three aspects of the cancer problem: ...
finally, as a summary statement, i would like to sum up the major points i have made.
let me just run over the key points again.
i'll briefly summarize the main issues.
in conclusion,¡
in closing,¡
in a word,¡
to sum up ...
in brief,¡
briefly.......
all in all,¡
finally,¡
as you can see, there are some very good reasons ...
to sum up, my conclusion is that the present program is the best one.
in conclusion ...
let me conclude my talk with the following comments.
allow me to conclude by listing out all the factors influencing the efficacy.
in conclusion, i would like to point out the following aspects.
i'd like to leave you with the following conclusion.
let me close by quoting dr. einstein, the famous physicist, who said that¡
i would like to come to a close by quoting what sir newton once said...
therefore, i would suggest that we...
i'd like to suggest...
as far as i'm concerned, the only solution to the problem is...
that's all, thank you.
that's the end of my presentation.
so much for my speech, thank you.
thank you for your attention.
thank you for your listening.
other expressions that may be useful in the end part of the speech
sorry, i see the red light is shining so i have to skip the last part and jump to the conclusion.
mr. chairman is signaling me, i have to stop here and leave out the remaining part to spare time.
we have proposed a framework of a hierarchical planning system for robots. first of all, the system is an automatic plan system that can guide the robot intelligently in terms of the environment. secondly, it is based on hierarchical planning. the planning problem has been hierarchically decomposed into two sub-problems: global destination selection and local motion planning. and finally, the simulation and application has proved it as an effective design.
(show the last visual)
that's all for my presentation. for any question to be raised, i'm quite willing to discuss them with you at any time. thank you, every one.
finally, we can draw the conclusion: edge detection and denoising are two important branches of image processing. if we combine edge detection with denoising, we can overcome the shortcomings of the commonly-used denolsing methods and without blurring the edge notably.
furthermore, there are many denoising and edge detection methods now. different methods are suitable for different types of images and noise models. we can do further research on how to combine these various denoising and edge detection methods according to the content of the images and nature of noise.
that's all for my talk. if you have any questions, please do not hesitate to ask me. i'm quite willing to discuss them with you at any time, thank you.
that's all t wanted to show you about machine vision and one of its applications, agv. thank you!
(turn to 12th ppt) ok, that is all i'm going to talk today.
thank you !
that's all. thank you!
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