IS4 - WRONG

A detailed diagram illustrating Intelligent Vision Systems with elements like cameras, data processing, and AI algorithms, bright and visually appealing, focusing on technology and machine learning

Intelligent Vision Systems Quiz

Test your knowledge on Intelligent Vision Systems and machine learning concepts with our engaging quiz! Whether you're a student or a professional, this quiz will help you reinforce your understanding of key principles.

Topics covered include:

  • Data leakage scenarios
  • Deep learning performance metrics
  • Classifier properties
  • AI regulation in the EU
15 Questions4 MinutesCreated by AnalyzingData42
Referring to the class discussion on data leakage what is the worst situation?
The unwanted leakage of data from training dataset to test data set
The unwanted leakage of data from test dataset to training data set since you are subtracting data to the generalization test, making the situation more optimistic
None of the other options since transferring data from test and/or training dataset is normal when the accuracy of the model is tested
The unwanted leakage of data from test dataset to training data set since you are subtracting data to the generalization test, making the situation more pessimistic
According to the class discussion, considering the training of deep learning models on standard CPUs and standard commercial GPUs boards, what is the gain in training performance (time) and efficiency (energy) for a medium/large-size project?
About 100x in performance and 10x in efficiency
More than 100x in performance and more than 5x in efficiency
About 10x in performance and 5x in efficiency
About 2x in performance and 2x in efficiency
A basic industrial setup for Intelligent vision systems is typically composed by the following elements:
Standard industrial camera with optics, processing HW and SW units, illumination system
Standard industrial smart camera with optics, external processing HW and SW units, illumination system
Standard industrial camera with optics, illumination system
None of the other options
According to the class discussion, what is the classifier with the following properties: - not based on neural techniques; - it’s deterministic with no random initialization; - perfect repeatability; - a minimum number of parameters is needed; learning is very simple but effective; - perfect explain ability
KNN
Linear classifier
Decision Tree
K-means
None of the other options
According to the class discussion, what kind of activity can be performed on the test set?
Mean test error estimation
Mean test error estimation and stardad deviation
All the answer
Confusion matrix test
The following activity: a) Data Selection; b) Data Filtering; c) Data Enhancing…
Are part of the classical machine learning approaches and they are (corretly) no longer used in deep learning applications
Contribute to keep lower the complexity of the learning task
Normal acrivities & lower complexity
Are part of the jon of the artificial intellient specialist in normale activities
According to the class discussion the kNN classifier, what kind of learning is it?
Instance-based Learning
Hard-limited Learning
None of the answer
Eager Learning
Unsupervised Clustering
An AI model is processing an input RGB image to evaluate the age expressed in year of the face present in the image. What kind of the model is it?
Classifier Model
Regressior Model
Clustering Model
Reinforced Learning Model
Non of the Above
According to the class discrussion, the theory of Intelligent Systems should incloude the folloquing designing steps
Representation
Representation, evaluation
Represtentations, evaluations, optimization
Non of the other options
Clustering alway requires a supervised dataset
True
False
According to the class discussion, using a blackbox solution is
Bad practice for a ML designer
Can be used under specific circumstances
Sinse all state of the art moels tend to be quite large and unexplainable, it is current good practice to adopt the black box approach since tou get the best model
According to the class discussion to the classifications systems and their decision boundaries, it is possibile uin general to optimize during the training/optimization step
The accuracy
The margin
Both
According to the class discussion about AI regulation in EU, the regualtion approach is based
Lost of use cases
Risk assessment of the application
Both
None of the ather options
According to the discussion presented in class, the EU regulatory framework for AI is:
Mainly focused on public services
Mainly focused on healt-related applications
Mainly focus on data privacy
Non of the other options
Considering the possible Intelligent Vision tasks which is the correct option?
Instance Segmentation is more complex than Object Detection
. Instance Segmentation is less complex than Object Detection
Instance Segmentation and Object Detection have a similar complexity
The other options are not Intelligent Vision tasks
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