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Computer Vision Intern Interview Questions

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1,050 computer vision intern interview questions shared by candidates

- Write a function to produce the convolution of an image with a filter - Write a function that fills a buffer with a rolling set of image object segmentation results - From a set of loss functions like L2 loss or hinge loss, explain which ones are rotationally invariant, sensitive to rescalings of the input features, and which are convex. - Given a set of standard random forest trees and a set of gradient boosted trees, explain how the model's predictions would change if you remove the first tree, the last tree, or make other changes after training. - Talk about a system design you've worked on where a web service provides computer vision computations on input images. How did you test it? How did you deploy it? - Given a pandas DataFrame with some numeric columns, how to produce counts of data for different category IDs, including with or without extra processing to remove noisy, missing, or outlier data points.
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Senior Computer Vision Engineer

Interviewed at NETGEAR

2.8★
May 5, 2018

- Write a function to produce the convolution of an image with a filter - Write a function that fills a buffer with a rolling set of image object segmentation results - From a set of loss functions like L2 loss or hinge loss, explain which ones are rotationally invariant, sensitive to rescalings of the input features, and which are convex. - Given a set of standard random forest trees and a set of gradient boosted trees, explain how the model's predictions would change if you remove the first tree, the last tree, or make other changes after training. - Talk about a system design you've worked on where a web service provides computer vision computations on input images. How did you test it? How did you deploy it? - Given a pandas DataFrame with some numeric columns, how to produce counts of data for different category IDs, including with or without extra processing to remove noisy, missing, or outlier data points.

HR was basically behavioral questions. One was a coding round. A simple dynamic programming question of find the minimum cost in a 2D grid. One was a simple debugging round that checked your knowledge of shallow copy with lists in python and some tensorflow API question. One brain teaser. Given a shape how would you make two cuts and re-arrange into a perfect square. The final interviewer asked some sort of data flow diagram for Lukas kanade optical flow.
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Computer Vision Video Systems Engineer

Interviewed at Qualcomm

3.8★
Jun 25, 2019

HR was basically behavioral questions. One was a coding round. A simple dynamic programming question of find the minimum cost in a 2D grid. One was a simple debugging round that checked your knowledge of shallow copy with lists in python and some tensorflow API question. One brain teaser. Given a shape how would you make two cuts and re-arrange into a perfect square. The final interviewer asked some sort of data flow diagram for Lukas kanade optical flow.

Questions about my projects listed on the resume. Assume you have a function that generates 1~5 with equal probability, how do you design a function to generate 1~8 with equal probability? How do you find the index of the target number in a sorted array? What if the array is rotated like [3,4,5,1,2]?
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AI Lab - Computer Vision Intern

Interviewed at ByteDance

3.4★
Apr 20, 2018

Questions about my projects listed on the resume. Assume you have a function that generates 1~5 with equal probability, how do you design a function to generate 1~8 with equal probability? How do you find the index of the target number in a sorted array? What if the array is rotated like [3,4,5,1,2]?

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