Any questions you want to practice should be geared towards your reliability, teamwork, and ability to follow instructions. Various industries should also be looking for motivation and enthusiasm for the specific position. You need to know some of the most common questions asked in interviews shared by Pritish Kumar Halder.
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Try practicing some of these common Image Analysis Scientists’ job interview questions:
1. Can you define overfitting and discuss ways to correct it?
How to answer: This is a common machine learning topic. The question is meant to gauge your knowledge of data modeling. The question contains two parts and asks you to define an issue and provide potential solutions. A question such as this one can help an interviewer understand your technical knowledge and problem-solving skills.
Answer: “Overfitting is a situation in which the model is too specific and not generalized. The model offers specific detail but misses the overall patterns and trends within the data. Some indications of overfitting appear when the training set is accurate but the test accuracy is unpredictable. Often, the test accuracy is much lower than the accuracy in the training set. This can be an indication of the model requiring adjustment.
You can fix overfitting by recalibrating the model to make it more broadly defined. Rather than having the model focus too much on details, you focus more on general trends. Adding in more data is one way to address overfitting. The broadening of the data you collect can eliminate the issue. Another potential way to address overfitting is in the model itself. Perhaps the model is overly complex and, therefore, focuses on the wrong things. In this type of situation, trying a less complex model sometimes corrects overfitting.”
2. What is image segmentation, and why is it necessary?
How to answer: This is a basic question regarding image analysis. An interviewer seeks to discover how knowledgeable you are regarding this topic and whether you have worked with image segmentation in the past. An effective answer allows you to demonstrate your knowledge with examples and integrate your experience into a response.
Answer: “Image segmentation is the process of partitioning an image into smaller parts. By using image segmentation, you can make the image easier to analyze. Image segmentation is an initial step in analyzing an image. Without image segmentation, further analysis might prove challenging.
For example, I worked on facial recognition software for a large cell phone company. The software used image segmentation to divide faces into smaller images, focusing on the different features. By accomplishing this, the device can recognize the individual image features that comprise the owner’s face. The software also recognizes when someone doesn’t have that combination of features, leaving the phone protected from someone else using it.”
3. What is contextual image classification?
How to answer: This question relates to computer vision and represents another layer of technical understanding of image processing and analysis. It’s important to define what image classification is before sharing some of your examples and experiences with image classification.
Answer: “In computer vision, contextual image classification refers to a kind of pattern recognition. Essentially, the system classifies images based on contextual information the computer interprets. For example, the system analyzes an image’s pixels and surrounding pixels nearby to create context. If you want to analyze images of homes, the computer can distinguish what image is the house and what surrounding scenery is based on the borders and neighboring pixels.
By comparison, segmentation does not use contextual information and sometimes can have unwanted variations in the data. I worked on a project once where we needed a detailed analysis of images, and we used contextual image classification to remove unwanted imagery and data from the sample.”
Not every question you will encounter when interviewing for the Image Analysis Scientists position will be related to a digital service supportive job. But those are the common topics interviewer can ask for selecting a qualified candidate.
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Composed by: Suma Sarker
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