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What would be a valid/substantial achievement in a Masters project (~30 pages, 4 months) in Computer Vision/Deep Learning?

Obviously it is not enough to just take an existing model (e.g. Mask R-CNN or similar), find/hack a dataset by yourself, add a layer or two out-of-the-box and finetune the model to it.

It is also obvious it can't be a huge contribution simple due to the size/nature of the project.

I'm thinking along the lines of implementing a new problem-specific loss function/accuracy metric, writing a new layer with custom functionality, and improvement of accuracy on a benchmark dataset.

closed as off-topic by Scott Seidman, Solar Mike, penelope, FuzzyLeapfrog, user3209815 Mar 26 at 14:56

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    This is something to discuss with your supervisor - we have no idea of what you have studied to what level and whether that topic is even relevant. – Solar Mike Mar 26 at 12:29
  • @SolarMike thanks, I'm not a student. I didn't mean this in a specific way. There should be some criteria on the degree of contribution, I believe. – Alex Mar 26 at 12:39
  • But those criteria would most likely only be known to specialists in the field. You need more field specific advice than can likely be found here. – Buffy Mar 26 at 13:21
  • If you aren't a student, why mention MSc and tag it as Masters? You need to find an advisor, I think. – Buffy Mar 26 at 13:28
  • I'd disagree with your comment about using an existing model, since my MS was pretty much that -- apply an existing model to a problem it seemed well suited for, show that the results were miserable, hack it, show that didn't improve things, offer ideas for future study. Even got a conference paper out of it. – Kathy Mar 26 at 14:13
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What would be a valid/substantial achievement in a Masters project (~30 pages, 4 months) in Computer Vision/Deep Learning?

Whatever satisfies the people who actually certify the master's project in question. In my department, that would be the student's advisor (and, as a formality, the department's director of graduate studies). In other departments, that would be a committee.

Different departments and even different individual faculty, even in the same subsubfield, apply different standards for what is "valid" or "substantial", just as different publication venues (and different individual reviewers), even in the same subsubfield, apply different standards for what is "publishable".

In particular, departments necessarily set standards that are realistic for the actual population of students that they admit. Baseline expectations at MIT may be wildly unrealistic at the University of Southern North Dakota at Hoople.

Different departments (and even different faculty) also have different philosophies about what the proper goal of a master's project should be. Should it be a body of publishable research? (Or more strictly, should it be a publication at a top-tier international conference like IMCL or NeurIPS, or at least a significant chunk thereof?) Or is it sufficient to produce a useful piece of software, say for an industry client, or a well-written expository survey? Or is it sufficient to attempt publishable research and settle for a useful implementation or survey?

Obviously it is not enough to just take an existing model (e.g. Mask R-CNN or similar), find/hack a dataset by yourself, add a layer or two out-of-the-box and finetune the model to it.

No, that is not obvious. In some departments, that would be considered a valid Master's project. In my opinion, it wouldn't be a very good Master's project, but my opinion only matters for students in my department.

  • thanks for the input. Could you elaborate what constitutes a good MS project in your opinion? – Alex Mar 26 at 14:50

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