35 + Interview Questions in Image Classification in Important Topics Page 1 InterviewSolution

1.	The scale-invariant feature transform can be used to detect and describe local features in images.
Answer» The SCALE invariant feature transform can be USED to detect and DESCRIBE local FEATURES in images. Choose the correct ANSWER from below options (1)False (2)True Answer:-(2)True

Discussion

2.	Neural network consists of __________ different layers
Answer» NEURAL network consists of __________ DIFFERENT layers Choose the CORRECT answer from below options (1)8 (2)1 (3)9 (4)5 (5)3 Answer:-(5)3

Discussion

3.	SIFT stands for ________________
Answer» SIFT stands for ________________ Choose the correct answer from below options (1)Scale Invariant FEATURE Tool (2)Scale INCREMENT Feature TRANSFORM (3)Scale Information Feature Transform (4)Scale Invariant Feature Transform Answer:-(4)Scale Invariant Feature Transform

Discussion

4.	________________________ is the number of correct predictions that the occurrence is positive
Answer» ________________________ is the number of CORRECT predictions that the occurrence is POSITIVE Choose the correct answer from below OPTIONS (1)False Positive (2)True NEGATIVE (3)True Positive (4)False Negative Answer:-(3)True Positive

Discussion

5.	The process of changing the pixel intensity values to achieve consistency in dynamic range for images is ___________.
Answer» The process of changing the pixel INTENSITY values to achieve CONSISTENCY in dynamic RANGE for images is ___________. Choose the correct answer from below options (1)EDGE DETECTION (2)Image normalisation (3)Image segmentation (4)Image denoising Answer:-(2)Image normalisation

Discussion

6.	Data Partitioning will help us to know efficiency of model
Answer» Data Partitioning will help us to know EFFICIENCY of model Choose the correct answer from below OPTIONS (1)FALSE (2)TRUE Answer:-(2)TRUE

Discussion

7.	ZCA results in ___________
Answer» ZCA results in ___________ Choose the CORRECT answer from below options (1)more correlation of FEATURES DIFFERENT variance (2)less correlation of features different variance (3)more correlation with same variance (4)less corelation of feature with same variance (5)no correlation with different variance Answer:-(4)less corelation of feature with same variance

Discussion

8.	An input image can be converted into structured form through ___________
Answer» An input IMAGE can be CONVERTED into structured form through ___________ Choose the correct answer from below options (1)Feature Extraction (2)Image Analysis (3)PREPROCESSING (4)Classification Answer:-(2)Image Analysis

Discussion

9.	Allowing training data to be included in testing data will not give actual performance results
Answer» ALLOWING training DATA to be INCLUDED in testing data will not GIVE ACTUAL performance results Choose the correct answer from below options (1)True (2)False Answer:-(1)True

Discussion

10.	SVM is efficient on ___________
Answer» SVM is efficient on ___________ CHOOSE the CORRECT answer from below options (1)High DIMENSIONAL SPACES (2)Low Dimensional Spaces Answer:-(1)High Dimensional Spaces

Discussion

11.	The major steps involved in image classification are ___________
Answer» The major steps involved in image classification are ___________ CHOOSE the correct answer from below options (1)None of the options (2)Input Image -> PREPROCESSING -> Feature Extraction -> Classification (3)Preprocessing -> Input Image -> Feature Extraction -> Classification (4)Input Image -> Preprocessing -> Classification -> Feature Extraction (5)Preprocessing -> Input Image -> Classification -> Feature Extraction Answer:-(2)Input Image -> Preprocessing -> Feature Extraction -> Classification

Discussion

12.	Neural Network do not consists of interconnected neurons where passing messages between each other is difficult
Answer» Neural Network do not consists of interconnected NEURONS where passing MESSAGES between each other is difficult Choose the correct answer from below OPTIONS (1)FALSE (2)TRUE Answer:-(1)FALSE

Discussion

13.	Classes in CIFAR-10 are dependent on each other
Answer» CLASSES in CIFAR 10 are dependent on each other Choose the correct ANSWER from below options (1)TRUE (2)FALSE Answer:-(2)FALSE

Discussion

14.	Allowing training data to be included in testing data will give actual performance results
Answer» ALLOWING training data to be included in testing data will GIVE actual PERFORMANCE results Choose the correct ANSWER from below options (1)TRUE (2)FALSE Answer:-(2)FALSE

Discussion

15.	Noise can be removed using Data Preprocessing
Answer» Noise can be removed using Data Preprocessing Choose the CORRECT answer from below options (1)FALSE (2)TRUE Answer:-(2)TRUE

Discussion

16.	ZCA stands for ___________
Answer» ZCA STANDS for ___________ Choose the correct answer from below options (1)Zero Phase Component Analysis (2)None of the Above (3)Zero Phase Analysis (4)Zero Phase CORRELATION Analysis (5)Zero Phase Covariance Analysis Answer:-(1)Zero Phase Component Analysis

Discussion

17.	The number of incorrect predictions that the occurrence is negative is False Negative
Answer» The NUMBER of incorrect predictions that the occurrence is negative is False Negative Choose the CORRECT answer from below OPTIONS (1)FALSE (2)TRUE Answer:-(2)TRUE

Discussion

18.	For SVM it is good to have ___________
Answer» For SVM it is good to have ___________ CHOOSE the correct answer from below options (1)NUMBER of DIMENSIONS > the number of samples (2)number of dimensions != the number of samples (3)number of dimensions = the number of samples (4)number of dimensions < the number of samples Answer:-(1)number of dimensions > the number of samples

Discussion

19.	___________________________ is defined as the percentage of correct predictions
Answer» ___________________________ is defined as the percentage of correct predictions Choose the correct answer from below options (1)Partioning The Data (2)Confusion Matrix (3)CROSS Validation (4)CLASSIFICATION Accuracy Answer:-(4)Classification Accuracy

Discussion

20.	In SVD, the matrix A of dimension m x n can be decomposed in to A=USVT, where V is a ___________.
Answer» In SVD, the MATRIX A of dimension m X n can be decomposed in to A USVT, where V is a ___________. CHOOSE the correct answer from below options (1)n x n orthonormal matrix (2)m x m Identity matrix (3)m x n matrix (4)m x m skew symmetric matrix Answer:-(1)n x n orthonormal matrix

Discussion

21.	In cross validation, the number of samples used for training the model is _____________
Answer» In cross validation, the number of samples used for training the model is _____________ CHOOSE the correct ANSWER from below options (1)increased (2)same (3)DECREASED (4)not used (5)used based on scenario Answer:-(3)decreased

Discussion

22.	The main aim of using SIFT for feature extraction is to obtain features that are very sensitive to changes in scale, rotation, image resolution, illum
Answer» The main AIM of using SIFT for feature extraction is to obtain features that are very sensitive to changes in scale, ROTATION, image resolution, illumination, etc. Choose the correct answer from below options (1)TRUE (2)FALSE Answer:-(2)FALSE

Discussion

23.	The main aim of using SIFT for feature extraction is to obtain features that are not sensitive to changes in scale, rotation, image resolution, illumi
Answer» The main aim of using SIFT for feature extraction is to obtain features that are not sensitive to changes in scale, rotation, image resolution, illumination, etc. Choose the correct answer from below OPTIONS (1)TRUE (2)False Answer:-(1)True

Discussion

24.	Data Preprocessing is a step the raw data is converted into a form suitable for subsequent analysis
Answer» Data Preprocessing is a step the RAW data is converted into a form suitable for subsequent analysis Choose the correct ANSWER from below options (1)FALSE (2)True Answer:-(2)True

Discussion

25.	CNN is a algorithm in which it comes under
Answer» CNN is a algorithm in which it comes under Choose the correct answer from below OPTIONS (1)DEEP LEARNING (2)Machine Learning (3)None of the mentioned (4)All the Options Answer:-(1)Deep Learning

Discussion

26.	The data is split into _________ sets
Answer» The DATA is SPLIT into _________ sets Choose the correct ANSWER from below options (1)1 (2)2 (3)3 (4)5 (5)4 Answer:-(3)3

Discussion

27.	Scikit Learn is an machine learning python package.
Answer» Scikit Learn is an machine learning PYTHON package. Choose the correct answer from below OPTIONS (1)True (2)False Answer:-(1)True

Discussion

28.	Conventional classification algorithms on image data
Answer» CONVENTIONAL classification algorithms on image data Choose the CORRECT answer from below OPTIONS (1)gives significant ACCURACY (2)COULD not give significant accuracy Answer:-(2)could not give significant accuracy

Discussion

29.	The steps involved in building a classification model are
Answer» The steps involved in building a CLASSIFICATION model are Choose the correct ANSWER from below options (1)INITIALIZE---->Train---->Evaluate--->Predict (2)Train---->Initialize---->Evaluate---> Predict (3)Initialize---->Train---->Predict---> Evaluate (4)Train---->Initialize---->Predict--->Evaluate Answer:-(3)Initialize---->Train---->Predict---> Evaluate

Discussion

30.	Singular values obtained from the SVD process utilizes ___________
Answer» Singular values obtained from the SVD process utilizes ___________ CHOOSE the CORRECT answer from below options (1)LOW Storage Space (2)High Storage Space Answer:-(1)Low Storage Space

Discussion

31.	A normalized image has ___________
Answer» A normalized IMAGE has ___________ Choose the CORRECT answer from below options (1)MEAN = 0 and variance = 1 (2)mean = 1 and variance = 1 (3)Mean = 0 and variance = 0 (4)mean = 1 and variance = 0 Answer:-(1)Mean = 0 and variance = 1

Discussion

32.	True Positive is when _____________
Answer» True POSITIVE is when _____________ CHOOSE the correct answer from below OPTIONS (1)The predicted instance and the actual instance are negative (2)The predicted instance and the actual instance are different (3)The predicted instance and the actual instance are UNKNOWN (4)The predicted instance and the actual instance are not negative Answer:-(4)The predicted instance and the actual instance are not negative

Discussion

33.	In the SVD method, a digital image is decomposed into ________ matrices
Answer» In the SVD method, a digital image is DECOMPOSED into ________ matrices Choose the correct answer from below OPTIONS (1)4 (2)8 (3)5 (4)3 (5)9 Answer:-(4)3

Discussion

34.	Normalization is the process of converting ___________
Answer» Normalization is the process of converting ___________ Choose the correct ANSWER from below options (1)All the options (2)pixel values to NORMAL state (3)pixel values to orthogonal COMPONENTS (4)None of the mentioned (5)normal state to pixel values Answer:-(2)pixel values to normal state

Discussion

35.	CIFAR-10 image dataset consists of ____________ training data and _____________ testing data
Answer» CIFAR 10 image dataset consists of ____________ training DATA and _____________ testing data Choose the correct answer from below options (1)10000,50000 (2)20000,40000 (3)50000,10000 (4)40000,20000 (5)30000,30000 Answer:-(3)50000,10000

Discussion

Explore topic-wise InterviewSolutions in .

The scale-invariant feature transform can be used to detect and describe local features in images.

Neural network consists of __________ different layers

SIFT stands for ________________

________________________ is the number of correct predictions that the occurrence is positive

The process of changing the pixel intensity values to achieve consistency in dynamic range for images is ___________.

Data Partitioning will help us to know efficiency of model

ZCA results in ___________

An input image can be converted into structured form through ___________

Allowing training data to be included in testing data will not give actual performance results

SVM is efficient on ___________

The major steps involved in image classification are ___________

Neural Network do not consists of interconnected neurons where passing messages between each other is difficult

Classes in CIFAR-10 are dependent on each other

Allowing training data to be included in testing data will give actual performance results

Noise can be removed using Data Preprocessing

ZCA stands for ___________

The number of incorrect predictions that the occurrence is negative is False Negative

For SVM it is good to have ___________

___________________________ is defined as the percentage of correct predictions

In SVD, the matrix A of dimension m x n can be decomposed in to A=USVT, where V is a ___________.

In cross validation, the number of samples used for training the model is _____________

The main aim of using SIFT for feature extraction is to obtain features that are very sensitive to changes in scale, rotation, image resolution, illum

The main aim of using SIFT for feature extraction is to obtain features that are not sensitive to changes in scale, rotation, image resolution, illumi

Data Preprocessing is a step the raw data is converted into a form suitable for subsequent analysis

CNN is a algorithm in which it comes under

The data is split into _________ sets

Scikit Learn is an machine learning python package.

Conventional classification algorithms on image data

The steps involved in building a classification model are

Singular values obtained from the SVD process utilizes ___________

A normalized image has ___________

True Positive is when _____________

In the SVD method, a digital image is decomposed into ________ matrices

Normalization is the process of converting ___________

CIFAR-10 image dataset consists of training data and _ testing data

Explore topic-wise InterviewSolutions in .

The scale-invariant feature transform can be used to detect and describe local features in images.

Neural network consists of __________ different layers

SIFT stands for ________________

________________________ is the number of correct predictions that the occurrence is positive

The process of changing the pixel intensity values to achieve consistency in dynamic range for images is ___________.

Data Partitioning will help us to know efficiency of model

ZCA results in ___________

An input image can be converted into structured form through ___________

Allowing training data to be included in testing data will not give actual performance results

SVM is efficient on ___________

The major steps involved in image classification are ___________

Neural Network do not consists of interconnected neurons where passing messages between each other is difficult

Classes in CIFAR-10 are dependent on each other

Allowing training data to be included in testing data will give actual performance results

Noise can be removed using Data Preprocessing

ZCA stands for ___________

The number of incorrect predictions that the occurrence is negative is False Negative

For SVM it is good to have ___________

___________________________ is defined as the percentage of correct predictions

In SVD, the matrix A of dimension m x n can be decomposed in to A=USVT, where V is a ___________.

In cross validation, the number of samples used for training the model is _____________

The main aim of using SIFT for feature extraction is to obtain features that are very sensitive to changes in scale, rotation, image resolution, illum

The main aim of using SIFT for feature extraction is to obtain features that are not sensitive to changes in scale, rotation, image resolution, illumi

Data Preprocessing is a step the raw data is converted into a form suitable for subsequent analysis

CNN is a algorithm in which it comes under

The data is split into _________ sets

Scikit Learn is an machine learning python package.

Conventional classification algorithms on image data

The steps involved in building a classification model are

Singular values obtained from the SVD process utilizes ___________

A normalized image has ___________

True Positive is when _____________

In the SVD method, a digital image is decomposed into ________ matrices

Normalization is the process of converting ___________

CIFAR-10 image dataset consists of ____________ training data and _____________ testing data

CIFAR-10 image dataset consists of training data and _ testing data