Question 11 (Expert):
In Vision Transformers (ViT), how are image patches typically converted into input tokens for the transformer encoder?
A) Raw pixel values are used directly
B) Each patch is flattened and linearly projected
C) Patches are processed through a CNN first
D) Edge detection is applied before projection
#Python #ViT #ComputerVision #DeepLearning #Transformers
✅ By: https://t.me/DataScienceQ
In Vision Transformers (ViT), how are image patches typically converted into input tokens for the transformer encoder?
A) Raw pixel values are used directly
B) Each patch is flattened and linearly projected
C) Patches are processed through a CNN first
D) Edge detection is applied before projection
#Python #ViT #ComputerVision #DeepLearning #Transformers
✅ By: https://t.me/DataScienceQ
❤1
Question 24 (Advanced - NSFW Detection):
When implementing NSFW (Not Safe For Work) content detection in Python, which of these approaches provides the best balance between accuracy and performance?
A) Rule-based keyword filtering
B) CNN-based image classification (e.g., MobileNetV2)
C) Transformer-based multimodal analysis (e.g., CLIP)
D) Metadata analysis (EXIF data, file properties)
#Python #NSFW #ComputerVision #DeepLearning
✅ By: https://t.me/DataScienceQ
When implementing NSFW (Not Safe For Work) content detection in Python, which of these approaches provides the best balance between accuracy and performance?
A) Rule-based keyword filtering
B) CNN-based image classification (e.g., MobileNetV2)
C) Transformer-based multimodal analysis (e.g., CLIP)
D) Metadata analysis (EXIF data, file properties)
#Python #NSFW #ComputerVision #DeepLearning
✅ By: https://t.me/DataScienceQ
❤2
Question 26 (Intermediate - Edge Detection):
In Python's OpenCV, which of these edge detection techniques preserves edge directionality while reducing noise?
A)
B)
C)
D)
#Python #OpenCV #EdgeDetection #ComputerVision
✅ By: https://t.me/DataScienceQ
In Python's OpenCV, which of these edge detection techniques preserves edge directionality while reducing noise?
A)
cv2.Laplacian() B)
cv2.Canny() C)
cv2.Sobel() with dx=1, dy=1 D)
cv2.blur() + thresholding #Python #OpenCV #EdgeDetection #ComputerVision
✅ By: https://t.me/DataScienceQ
Are you preparing for AI interviews or want to test your knowledge in Vision Transformers (ViT)?
Basic Concepts (Q1–Q15)
Architecture & Components (Q16–Q30)
Attention & Transformers (Q31–Q45)
Training & Optimization (Q46–Q55)
Advanced & Real-World Applications (Q56–Q65)
Answer Key & Explanations
#VisionTransformer #ViT #DeepLearning #ComputerVision #Transformers #AI #MachineLearning #MCQ #InterviewPrep
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🚀 Comprehensive Guide: How to Prepare for an Image Processing Job Interview – 500 Most Common Interview Questions
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#ImageProcessing #ComputerVision #OpenCV #Python #InterviewPrep #DigitalImageProcessing #MachineLearning #AI #SignalProcessing #ComputerGraphics
Let's start: https://hackmd.io/@husseinsheikho/IP
#ImageProcessing #ComputerVision #OpenCV #Python #InterviewPrep #DigitalImageProcessing #MachineLearning #AI #SignalProcessing #ComputerGraphics
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