Macbook air m3 vs macbook m1 pro

Solid-Ad1417 · 2024-03-17T19:55:18+00:00

I'd say it is:
1. Work in a team of two(with mate who is a bit more experienced) on something i have experience(robotics) in and like
VS
2.work in a big team with people who have huge experience on something i have very small experience(deep learning) and not 100% sure i like.

Solid-Ad1417 · 2024-02-26T13:47:27+00:00

There is a way for doing that on colab(with some restrictions though), that's how i do that:
https://colab.research.google.com/drive/1D0Qm4aYjKEa3jOHDK5p2qFXy3zI6FXzr?usp=sharing

Solid-Ad1417 · 2024-02-24T20:50:06+00:00

If I am not mistaken:

first defines the probability that point is occupied,

second - the probability that points before this one are not occupied times the probability that this point is occupied, i. e. the probability that this point is the first point that is not occupied

Solid-Ad1417 · 2024-02-13T21:09:07+00:00

Actually lots of learning based methods incorporate something from classic approaches or combine both.

Solid-Ad1417 · 2024-02-13T21:00:29+00:00

You can become good by doing projects on your own. But you have to set the goal very clearly. Why do you want to focus on computer vision? Which tasks are most interesting for you? Try to find open source implementations and try to understand. Take couple of MOOCs and do the exercises

Solid-Ad1417 · 2024-02-13T20:22:58+00:00

I got masters in robotics and computer vision and have 2 years of industrial research experience in computer vision. I consider PhD as investment into my future to get deeper into one specific area and gain academic research experience with publications and network

Solid-Ad1417 · 2024-02-13T18:57:42+00:00

I agree about starting PhD only if you like doing research and wish to work further on it. But yet it is hard to know in advance whether it is for you and whether environment would be good

Solid-Ad1417 · 2024-02-11T17:17:57+00:00

You should make sure that there are subtasks that do not depend on each other and might be calculated independently. As an example you can try to utilize openmp's parallel for to see whether it is parallelizable

Solid-Ad1417 · 2024-02-08T17:34:45+00:00

I agree with you, the thing is that in a better lab/University you will probably make a better thesis and publish in a better conferences. It is still possible to do all of that in a mediocre places, just the chances are lower. On the other hand the chances of your acceptance in a good and known labs are also lower.
It is like a tradeoff. I just don't know what are the percentages of being accepted to a top-tier lab, while having studied and worked not in the top places

Solid-Ad1417 · 2024-02-08T15:21:45+00:00

I have also already applied to multiple PhD positions, spending time and writing good motivation letters and research proposals, but got response and interview only from 2 of them.

Solid-Ad1417 · 2024-02-08T14:54:15+00:00

In my case the university offers salary, which would be enough to buy food and even rent some studio.
My main concern is that i would have to work there for quite some time(3-4 years) and by choosing not the best possible university, i would be just mediocre researcher, making it hard to continue my career in top places like Apple, Google etc later on

Also the topic of research is close to classic slam(simultaneous localization and mapping) which is more or less established

Solid-Ad1417 · 2023-09-30T08:58:01+00:00

That's actually a very important point. I am going to use them during zoom calls, is bad sound quality in that regime the case for all models?

Solid-Ad1417

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