Computer Vision Expert

Description

Interview questions for Computer Vision Expert

Interview Questions (96)

Q1What specific algorithms or data structures tend to show up more often in CV/ML coding rounds?
Technical
Q2How often do interviewers ask about CV concepts or ML fundamentals, and what areas should I prioritize?
Technical
Q3Are system design interviews common for senior CV/ML roles, and if so, what should I prepare for?
Technical
Q4What does success look like here this year?
Reverse
Q5What is the difference between image recognition and object detection?
Technical
Q6Can you explain what a convolutional neural network (CNN) is and how it works?
Technical
Q7How is a vision transformer different from a CNN?
Technical
Q8Explain the key challenges of computer vision in autonomous vehicles.
Situational
Q9How would you improve a real-time object classification system for accuracy and speed?
Situational
Q10Given an imbalanced data set, how would you train a model to accurately classify images?
Situational
Q11What is semi-supervised machine learning?
Technical
Q12How do you choose which algorithm to use for a dataset?
Technical
Q13Explain the K Nearest Neighbor algorithm.
Technical
Q14What is feature importance in machine learning, and how do you determine it?
Technical
Q15What is overfitting in machine learning, and how can it be avoided?
Technical
Q16What are the key differences between supervised and unsupervised learning?
Technical
Q17What is a confusion matrix, and why is it useful?
Technical
Q18What is the difference between parametric and non-parametric models?
Technical
Q19What is the bias-variance tradeoff in machine learning?
Technical
Q20Is it true that we need to scale our feature values when they vary greatly?
Technical
Q21The model you have trained has a low bias and high variance. How would you deal with it?
Situational
Q22What is Model Drift and how do you detect it in production?
Technical
Q23Which cross-validation technique would you suggest for a time-series dataset and why?
Technical
Q24Why can the inputs in computer vision problems get huge? Explain it with an example.
Technical
Q25When you have a small dataset, suggest a way to train a convolutional neural network.
Technical
Q26What is the state-of-the-art object detection algorithm YOLO, and how has its architecture evolved recently?
Technical
Q27Explain the concept of pixels and image resolution.
Technical
Q28What are the common color spaces used in image processing (RGB, HSV, LAB, YCbCr)?
Technical
Q29Explain the 2D Discrete Fourier Transform (DFT).
Technical
Q30How does the Fast Fourier Transform (FFT) improve over DFT?
Technical
Q31What is convolution in image processing and why is it important?
Technical
Q32What is correlation and how does it differ from convolution?
Technical
Q33What are linear and non-linear filters? Give examples.
Technical
Q34Explain Gaussian filtering and its purpose.
Technical
Q35What are some commonly used image enhancement techniques?
Technical
Q36What is histogram equalization and how does it enhance images?
Technical
Q37Explain the concept of color correction and its applications.
Technical
Q38What is image thresholding, and how does Otsu's method work?
Technical
Q39What are the different types of noise that can occur in images?
Technical
Q40Explain different noise reduction techniques.
Technical
Q41What is Principal Component Analysis (PCA) and how is it used in image processing?
Technical
Q42What are Affine Transformations in images?
Technical
Q43What are geometric transformations in image processing?
Technical
Q44What is a homography, and where is it used?
Technical
Q45What are camera intrinsic and extrinsic parameters, and why is camera calibration needed?
Technical
Q46What is epipolar geometry, and how is it used in stereo vision?
Technical
Q47What are morphological operations and why are they useful?
Technical
Q48What is the morphological gradient?
Technical
Q49What is an edge in an image?
Technical
Q50Explain Sobel and Prewitt edge detectors.
Technical
Q51Explain the Canny edge detection algorithm step by step.
Technical
Q52Explain the Hough Transform and its use in detecting lines and circles.
Technical
Q53What is the Harris Corner Detector, and how does it differ from the FAST detector?
Technical
Q54What is a feature descriptor in computer vision?
Technical
Q55What is Scale-Invariant Feature Transform (SIFT) and how does it work?
Technical
Q56Explain Speeded Up Robust Features (SURF).
Technical
Q57What is ORB and how does it compare to SIFT and SURF?
Technical
Q58What is the Histogram of Oriented Gradients (HOG) and how is it used?
Technical
Q59Explain template matching and its limitations.
Technical
Q60What is optical flow? Explain Lucas-Kanade method.
Technical
Q61What is object tracking, and how do algorithms like Kalman Filter, SORT and DeepSORT work?
Technical
Q62What is the Watershed algorithm, and how is it used for image segmentation?
Technical
Q63How can image segmentation be performed using K-Means clustering?
Technical
Q64What is an image? What are pixels, channels, bit depth?
Technical
Q65What is normalization in image preprocessing and why is it used?
Technical
Q66What is a convolution operation in image processing?
Technical
Q67Explain padding, stride, and dilation.
Technical
Q68What are kernels/filters? Give examples (Sobel, Laplacian, Gaussian).
Technical
Q69What’s the difference between high-pass and low-pass filters?
Technical
Q70What is affine vs perspective transformation?
Technical
Q71What is a descriptor? How is it used for matching?
Technical
Q72What is a convolutional neural network (CNN)?
Technical
Q73What is receptive field? How does it grow?
Technical
Q74What are BatchNorm and Dropout doing?
Technical
Q75What problem does skip/residual connection solve?
Technical
Q76What is a transposed convolution? Why does it increase resolution?
Technical
Q77What is EfficientNet? How does compound scaling work?
Technical
Q78What is Vision Transformer (ViT)? How does it differ from CNNs?
Technical
Q79How does YOLO work?
Technical
Q80What is Non-Max Suppression (NMS)? Why is it needed?
Technical
Q81What’s the role of RPN (Region Proposal Network) in Faster R-CNN?
Technical
Q82What’s the difference between semantic, instance, and panoptic segmentation?
Technical
Q83How does U-Net work? What are skip connections for?
Technical
Q84What is stereo vision? Epipolar geometry?
Technical
Q85What is PSNR and SSIM? How are they computed?
Technical
Q86What is super-resolution? Explain bicubic vs CNN-based methods.
Technical
Q87How do you deploy a CV model in production?
Technical
Q88How do you handle image data pipelines (augmentation, caching, batching)?
Technical
Q89How do you optimize inference latency?
Technical
Q90Explain how mAP is calculated.
Technical
Q91What is Contrastive Learning?
Technical
Q92What is diffusion model / Stable Diffusion?
Technical
Q93How do you fine-tune a pre-trained model for a new dataset?
Technical
Q94How would you design a segmentation network for satellite imagery?
Situational
Q95How do you handle class imbalance in object detection?
Situational
Q96If your segmentation mask is misaligned, how would you debug it?
Situational