Object Recognition Question & AnswersJuly 7, 2021 By WatElectronics This article lists 100+ Object Recognition MCQs for engineering students. All the Object Recognition Questions & Answers given below includes solution and link wherever possible to the relevant topic.Rational function tester will not recognize the objects with the help of look and feel, but it finds out the object with the help of properties and its values. When we execute a particular test will get a log file and that log file shows recognition failures and warnings. Object recognition will be divided into two parts, it finds outs the object based on the recognition weights and recognition thresholds. Object detection and object recognition are some of the common computer vision problems which deal with identifying and locating objects of certain classes in the image.There are three types of recognition are there in artificial intelligence they are content-based image retrieval, biometric identification, and handwriting recognition. The vision recognizes the activities and also objects. The telephone directory assistance is an application of the speech recognition domain. The model database, hypothesizer, feature detector, and hypothesis verifier are the components of an object recognition system. The Human and computer interface face recognition system is used in biometric identification, human and computer interfaces. In a face recognition system, the complications occur due to variations in facial expressions, pose, illumination, etc.1). How many types of recognition are there in artificial intelligence? One Two Three Four HintThere are three types of recognition are there in artificial intelligence they are content-based image retrieval, biometric identification, and handwriting recognition2). The vision recognizes the ______ Activities Object Both a and b None of the above HintThe vision recognizes the activities and also an objects3). The random variables are of _________ types One Two Three Four HintThe random variables are of three types they are continuous, discrete, and Boolean random variables4). _________ is an application of document image analysis Optical character recognition Junk mail filtering Information extraction All of the above HintOptical character recognition is an application of document image analysis5). _________ is an application of the speech recognition domain Optical character recognition Junk mail filtering Information extraction Telephone directory assistance HintTelephone directory assistance is an application of the speech recognition domain6). What is the standard form of ALPR? Automatic License Plate Recognition Automatic License Plate Reader License Plate Recognition None of the above HintThe standard form of ALPR is Automatic License Plate Reader7). _________ are the components of object recognition system Model database, hypothesizer Feature detector, hypothesis verifier Both a and b None of the above HintModel database, hypothesizer, feature detector, and hypothesis verifier are the components of an object recognition system8). The face recognition system used in _____ Biometric identification Human and computer interface Both a and b None of the above HintThe Human and computer interface face recognition system used in biometric identification, human and computer interface9). In a face recognition system the complications occur due to variations in ________ Facial expressions Pose Illumination All of the above HintIn a face recognition system the complications occur due to variations in facial expressions, pose, illumination, etc10). What is the standard form of ANPR? Automatic Number Plate Recognition Automatic Number Plate Reader License Plate Recognition None of the above HintThe standard form of ANPR is Automatic Number Plate Recognition11). The facial recognition uses _______ techniques Facial geometry Facial thermogram Skin pattern recognition, smile All of the above HintThe facial recognition uses facial geometry, facial thermogram, skin pattern recognition, and smile techniques12). Which one is a fingerprint matching technique? Pattern matching Minutiae-based matching Both a and b None of the above HintBoth pattern matching and minutiae-based matching are fingerprint matching techniques13). ________ is an application of the medical domain Optical character recognition Computer-aided diagnosis Fruit sorting None of the above HintCompute-aided diagnosis is an application of the medical domain14). ________ is an application of the remote sensing Optical character recognition Computer-aided diagnosis Fruit sorting Forecasting remote yield HintForecasting remote yield is an application of the remote sensing15). What is the standard form of LPR? License Plate Reader Automatic License Plate Reader License Plate Recognition None of the above HintThe standard form of LPR is License Plate Recognition16). What is the standard form of AVI? Automatic Volume Identification Automatic Vehicle Identification Automatic Voice Identification None of the above HintThe standard form of AVI is Automatic Vehicle Identification17). What is the standard form of MLPR? Mobile Plate Recognition Mobile License Plate Recognition Mobile License Plate Reader None of the above HintThe standard form of MLPR is Mobile License Plate Reader18). __________ are the applications of an object recognition Driverless cars Medical image processing Monitoring and surveillance All of the above HintDriverless cars, medical image processing, monitoring, and surveillance, etc are the applications of an object recognition19). ________ can be represented by using empirical frequency distributions or histograms Colors Texture Both a and b None of the above HintColors, textures can be represented by using empirical frequency distributions or histograms20). For studying object recognition ___________ learning provides a framework Supervised Unsupervised Both a and b None of the above HintFor studying object recognition supervised learning provides a framework21). How many approaches are there to perform object recognition using deep learning? One Two Three Four HintThere are two approaches are there to perform object recognition using deep learning they are training a model from scratch and using a pre-trained deep learning model22). The segmentations are of ____ types One Two Three Four HintThe segmentations are of two types they are instance and semantic segmentation23). __________ are the examples of object detection in real-time Tracking objects People counting Person detection All of the above HintTracking objects, people counting, person detection are examples of object detection in real-time24). __________ are the difficulties in object recognition under varied circumstances Lighting, rotation, positioning Mirroring, occlusion, scale Both a and b None of the above HintLighting, rotation, positioning, mirroring, occlusion, scale is the difficulties in object recognition under varied circumstances25). _________ are the main tasks in object recognition Classification, tagging Detection, segmentation Both a and b None of the above HintClassification, tagging, detection, and segmentation are the main tasks in object recognitionObject Recognition MCQs for Quiz26). What is the standard form of CNN? Computer Neural Network Computer Network Neural Convolutional Neural Network None of the above HintThe standard form of CNN is Convolutional Neural Network27). Which one is an instance-based method of object recognition? Decision stump Random forest K-nearest neighbor None of the above HintK-Nearest Neighbor(K-NN) is an instance-based method of object recognition28). Which one comes under the decision tree learning method of object recognition? Bayesian belief network Random forest Linear discriminant analysis None of the above HintRandom forest comes under the decision tree learning method of object recognition29). Which one comes under the bayesian method of object recognition? Bayesian belief network Decision stump Random forest None of the above HintBayesian belief network comes under the bayesian method of object recognition30). What is the standard form of RBF? Radial Basis Fraction Radial Basis Function Radial Base Fraction None of the above HintThe standard form of RBF is Radial Basis Function31). What is the standard form of LDA? Linear Deep Learning Analysis Linear Determinant Analysis Linear Discriminant Analysis None of the above HintThe standard form of LDA is Linear Discriminant Analysis32). Which one comes under clustering methods of object recognition? K-means Expectation maximization Both a and b None of the above HintK-means and expectation-maximization both come under clustering methods of object recognition33). What is the standard form of SOM? Self Organizing Map Simple Organizing Map Self Organizing Machine None of the above HintThe standard form of SOM is Self Organizing Map35). __________ comes under artificial neural network Perception Backpropagation Hopfield network All of the above HintPerception, backpropagation, and Hopfield network comes under artificial neural network36). ________ are the deep learning methods of object recognition Restricted Boltzman Machine Deep belief networks Convolutional network, and stacked autoencoder All of the above HintRestricted Boltzman machine, deep belief networks, convolutional network, and stacked auto-encoder are the deep learning methods of object recognition37). What is the standard form of RBM? Regional Boltzman Machine Restricted Boltzman Machine Radial Boltzman Machine None of the above HintThe standard form of RBM is Restricted Boltzman Machine38). What is the standard form of LVQ? Linear Variant Quantization Linear Vector Quantization Non-linear Variant Quantization None of the above HintThe standard form of LVQ is Linear Vector Quantization39). What is the standard form of DBN? Deep Belief Networks Deep Boltzman Networks Discriminant Belief Networks None of the above HintThe standard form of DBN is Deep Belief Networks40). What is the standard form of HMM? Hidden Markov Model Hidden Markov Machine Hidden Machine Model None of the above HintThe standard form of HMM is Hidden Markov Model41). Which one is a type of neural network? Bayesian networks Linear networks Probabilistic networks All of the above HintBayesian networks, linear networks, probabilistic networks all are neural networks42). How many layers does a linear network have? One Two Three Four HintThe linear networks have two layers they are input layer and output layer43). _________ are the commonly used predictive data mining methods Decision trees, logistic regression Artificial neural networks, support vector machines Naive Bayes, Bayesian network, k nearest neighbor All of the above HintDecision trees, logistic regression, artificial neural networks, support vector machines, naive Bayes, Bayesian network, and k nearest neighbor are the commonly used predictive data mining methods44). __________ is an example of local discovering algorithm Naive Bayes Tree augmented naive Bayes Semi interleaved HITON PC All of the above HintSemi interleaved HITON PC is an example of the local discovering algorithm45). _________ are the examples of hybrid structure learning algorithms Max-min hill climbing Naive Bayes Tree augmented naive Bayes All of the above HintMax-min hill climbing is an example of hybrid structure learning algorithms46). ___________ are the example of constraint-based structure learning algorithms Grow shrink Hill climbing Tabu search All of the above HintGrow shrink is an example of constraint-based structure learning algorithms47). ___________ are the example of score-based structure learning algorithms Naive Bayes Hill climbing Both a and b None of the above HintHill climbing is an example of score-based structure learning algorithms48). __________ are the popular inference methods Clique tree propagation Variable elimination Recursive conditioning All of the above HintClique tree propagation, variable elimination, and recursive conditioning are the popular inference methods49). _______ are the Bayesian networks inference Parameter learning Structure learning Deducing unobserved variables All of the above HintParameter learning, structure learning, deducing unobserved variables are the Bayes networks inference50). __________ are the examples of generative models Naive Bayes clasifier SVM Boosted decision trees All of the above HintNaive Bayes classifier is an example of generative modelsObject Recognition MCQs for Students51). __________ are the examples of discriminative models Naive bayes clasifier SVM Bayesian network All of the above HintSVM is example of discriminative models52). ____________ are the typical associative classification methods CBA CMAR CPAR All of the above HintCBA, CMAR, CPAR are the typical associative classification methods53). What is the standard form of CMAR? Classification Based on Association Rules Classification Based on Multiple Association Rules Classification Based on Predictive Association Rules None of the above HintThe standard form of CMAR is Classification Based on Multiple Association Rules54). What is the standard form of CPAR? Classification Based on Predictive Association Recognition Classification Based on Periodic Association Rules Classification Based on Predictive Association Rules None of the above HintThe standard form of CPAR is Classification Based on Predictive Association Rules55). Which one is a deterministic algorithm? SVM Neural network Both a and b None of the above HintSVM is a deterministic algorithm56). The neural networks are _________ Relatively old Non-deterministic algorithm Easy to learn All of the above HintThe neural networks are relatively old, it is a non-deterministic algorithm, and it is very easy to learn57). The SVM is __________ Relatively new concept Deterministic algorithm Hard to learn All of the above HintThe SVM is a relatively new concept, it is a deterministic algorithm, and it is hard to learn58). _________ are the common applications of SVM Face detection Handwriting recognition Bioinformatics All of the above HintFace detection, Handwriting recognition, Bioinformatics are the common applications of SVM59). The mathematical portion used in bioinformatics are ______ Matrices, differentiation/integration Biostatistics Complex mathematics functions All of the above HintThe mathematical portion used in bioinformatics are matrices, differentiation/integration, biostatistics, and complex mathematics functions60). ________ are the properties of SVM Duality, kernels Margin, convexity Sparseness All of the above HintDuality, kernels, margin, convexity, sparseness are the properties of SVM61). Which one is a non-deterministic algorithm? SVM Neural network Both a and b None of the above HintNeural network is a non-deterministic algorithm62). The genetic algorithm composed of ___________ operators Reproduction Mutation Crossover All of the above HintThe genetic algorithm composed of reproduction, mutation, and crossover operators63). The advantages of genetic algorithms are ______ Easy to implement Easy to understand Good for noisy environments All of the above HintThe genetic algorithms are easy to implement and understand, and good for noisy environments64). The disadvantages of genetic algorithms are ______ Slower than some other methods Choosing fitness and encoding is difficult Takes a long time to find a near-optimal solution All of the above HintThe genetic algorithms are Slower than some other methods, choosing fitness and encoding is difficult, and it takes a long time to find a near-optimal solution65). The advantages of fuzzy logic are _________ Easy to analyze Low cost Easy to understand All of the above HintThe fuzzy logic are easy to analyze and understand and the cost of fuzzy logic is low66). The disadvantages of fuzzy logic are _________ Not stable Complex to design Only provides a crude sizing All of the above HintThe fuzzy logic are complex to design, not stable, and it only provides a crude sizing67). The advantages of artificial neural network are ________ Powerful Easy to use Alter to unknown conditions All of the above HintThe artificial neural network are powerful, easy to use, and alter to unknown conditions68). The disadvantages of artificial neural network are ________ Large complexity of network structure Difficult to know how many layers and neurons are necessary Learning can be slow All of the above HintIn artificial neural network complexity of network structure is large, difficult to know how many layers and neurons are necessary, and learning can be slow in an artificial neural network69). The configuration of fuzzy logic consists of _______ modules Knowledge base Decision-making logic Defuzzification interface, fuzzification interface All of the above HintThe configuration of fuzzy logic consists of a knowledge base, decision-making logic, defuzzification interface, and fuzzification interface modules70). An artificial intelligence used in _________ Communication Transportation Integrated applications All of the above HintAn artificial intelligence used in Communication, Transportation, and Integrated applications71). __________ are the applications of face detection Webcams that tracks the user Banking using ATM Biometrics/access control All of the above HintWebcams that tracks the user, Banking using ATM, Biometrics/access control, etc are the applications of face detection72). What is the standard form of FRCNN? First Convolutional Neural Network First Region Convolutional Neural Network Faster Region Convolutional Neural Network None of the above HintThe standard form of FRCNN is Faster Region Convolutional Neural Network73). What is the standard form of SSD? Single Shot Detector Simple Shot Detector Single Shot Multibox Detector None of the above HintThe standard form of SSD is Single Shot Multibox Detector74). What is the standard form of SVMs? Single Vector Machines Simple Vector Machines Support Vector Machines None of the above HintThe standard form of SVMs is Support Vector Machines75). _______ are the machine learning techniques SVM machine learning model Bag of words model Viola jones algorithm All of the above HintSVM machine learning model, Bag of words model, Viola jones algorithm are machine learning techniquesObject Recognition MCQs for Interviews76). What is the standard form of YOLO? You Only Look Once You Once Look Only You Look Once None of the above HintThe standard form of YOLO is You Only Look Once77). Which one is an application of neural networks? Data validation Risk management Both a and b None of the above HintData validation, and Risk management both are applications of neural network78). In __________ the decision nodes are represented Squares Circles Triangles Rectangle HintIn squares, the decision nodes are represented79). In __________ the chance nodes are represented Circles Triangles Rectangle Squares HintIn circles, the chance nodes are represented80). In __________ the end nodes are represented Circles Triangles Rectangle Squares HintIn triangles, the end nodes are represented81). In closed classes _________ objects are available One Two Three Four HintIn closed classes four objects are available they are conjunction, preposition, article, and pronoun82). In parsing ________ states are available One Two Three Four HintIn parsing three states are available they are goal test, initial test, and successor function83). Which method deals with a pattern? Decision theoretic method Structure method Both a and b None of the above HintDecision theoretic method and structure methods deals with a pattern84). The pattern recognition task consists of __________ steps One Two Three Four HintThe pattern recognition task consists of two steps they are feature selection and matching85). The classifiers categorized into ______ methods One Two Three Four HintThe classifiers categorized into two methods they are decision-theoretic methods, and structure methods86). __________ are the structural methods Matching shape numbers String matching Syntactic method All of the above HintMatching shape numbers, string matching, syntactic method are the structural methods87). What are the disadvantages of matching shape numbers? Mirror problem intensity b) c)d Color is unable to recognize Cannot use for a hallow structure All of the above HintIn matching shape numbers color is unable to recognize, and it cannot uses for a hallow structure, and another disadvantage is mirror problem intensity88). Which is a method of object recognition? Decision tree learning Bayesian Kernel methods All of the above HintDecision tree learning, Bayesian, and Kernel methods all are a method of object recognition89). The advantages of decision tree regression are _______ Very easy to interpret or visualize Works on both non-linear and linear problems No need to do feature scaling All of the above HintThe decision tree regression is very easy to interpret or visualize, works on both non-linear and linear problems, and there is no need to do feature scaling90). The random forest regression are ________ Very powerful Very accurate Very good performance for both non-linear and linear problems All of the above HintThe random forest regression is very powerful & accurate, and the performance is very good for both non-linear and linear problems91). The SVR _________ Works very well on non-linear problems Can be easily adapted Not biased by outliers All of the above HintThe SVR Works very well on non-linear problems, it can be easily adapted, and not biased by outliers92). The polynomial regression _________ Works on any size of data Works best for non-linear problems Both a and b None of the above HintThe polynomial regression works on any size of data and also works best for non-linear problems93). The linear regression _____________ Works with almost any kind of dataset Gives quite good information about the features Both a and b None of the above HintThe linear regression works with almost any kind of dataset and gives quite good information about the features94). The advantages of face detection are ________ Full automation High accuracy rates Improvement of security level All of the above HintThe full automation, high accuracy rates, improvement of security level are the advantages of face detection95). The disadvantages of SVR are ________ Not a familiar model Quiet difficult to understand Both a and b None of the above HintThe SVR is not a familiar model and it is quite difficult to understand96). The disadvantages of face detection are ______ Lower processing speed Surveillance angle Image size and quality All of the above HintIn face detection the processing speed is low, Surveillance angle, Image size, and quality are the disadvantages97). The disadvantages of decision tree regression are _______ Poor results on small datasets Overfitting can easily occur Both a and b None of the above HintIn decision tree regression the results on small datasets are poor and overfitting can easily occur in decision tree regression98). The template matching is sensitive to ______ Noise Occlusions Both a and b None of the above HintThe template matching is sensitive to noise and occlusions99). The pixel-level template matching is of _______ type One Two Three Four HintThe pixel-level template matching is of four types they are total templates, partial templates, piece templates, and flexible templates100). __________ are the template matching applications 3D reconstruction Motion detection Object recognition All of the above Hint3D reconstruction, motion detection, object recognition are the template matching applicationsRead more about Face Recognition Time is Up! Time's up