Object Detection and Recognition MCQs With Answers

Computer MCQs 360April 11, 2024

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Welcome to the Object Detection and Recognition MCQs with Answers. In this post, we have shared Object Detection and Recognition Online Test for different competitive exams. Find practice Object Detection and Recognition Practice Questions with answers in Computer Tests exams here. Each question offers a chance to enhance your knowledge regarding Object Detection and Recognition.

Object Detection and Recognition Online Quiz

By presenting 3 options to choose from, Object Detection and Recognition Quiz which cover a wide range of topics and levels of difficulty, making them adaptable to various learning objectives and preferences. You will have to read all the given answers of Object Detection and Recognition Questions and Answers and click over the correct answer.

Test Name: Object Detection and Recognition MCQ Quiz Practice
Type: Quiz Test
Total Questions: 40
Total Marks: 40
Time: 40 minutes

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Object Detection and Recognition

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1 / 40

Which feature descriptor is used in traditional object detection algorithms?

Speeded-Up Robust Features (SURF)

Histogram of Oriented Gradients (HOG) (correct)

Scale-Invariant Feature Transform (SIFT)

2 / 40

What is the primary challenge of object detection in crowded scenes?

Low image resolution

Limited computing resources

Overlapping objects (correct)

3 / 40

What does IoU stand for in object detection evaluation metrics?

Index of Utility

Intersection over Union (correct)

Input over Unit

4 / 40

Which object detection technique uses a Region Proposal Network (RPN) for generating proposals?

Faster R-CNN (correct)

YOLO

SSD

5 / 40

Which object detection algorithm introduces the concept of Feature Pyramid Networks (FPN)?

RetinaNet (correct)

SSD

YOLO

6 / 40

What does FPN stand for in object detection architectures?

Fast Processing Network

Feature Pyramid Network (correct)

Feature Propagation Network

7 / 40

What does SSD stand for in object detection?

Scale-Space Detection

Selective Search Detector

Single Shot MultiBox Detector (correct)

8 / 40

Which evaluation metric measures the accuracy of object detection algorithms?

Error Margin

Accuracy Rate

mAP (mean Average Precision) (correct)

9 / 40

What is the primary goal of Non-Maximum Suppression (NMS) in object detection?

Removing duplicate detections (correct)

Augmenting training data

Enhancing image resolution

10 / 40

Which technique combines object detection and image segmentation?

Mask R-CNN (correct)

YOLO (You Only Look Once)

Faster R-CNN

11 / 40

Which technique is used for real-time object detection on mobile devices?

VGGNet

MobileNet (correct)

ResNet

12 / 40

What is the purpose of the RoI pooling layer in object detection architectures?

Enhancing object recognition

Adjusting anchor box sizes

Extracting fixed-size features from RoIs (correct)

13 / 40

Which algorithm is commonly used for generating region proposals in object detection?

Selective Search (correct)

K-Means Clustering

Gaussian Mixture Model

14 / 40

Which algorithm is used for instance segmentation, where objects of the same class are individually segmented?

YOLO

Mask R-CNN (correct)

SSD

15 / 40

What is the primary advantage of using anchor-free object detection methods over anchor-based methods?

Simplicity in implementation (correct)

Lower memory usage

Higher accuracy

16 / 40

What is the primary use of anchor boxes in the YOLO algorithm?

Adjusting object size

Enhancing image resolution

Defining grid cells for object localization (correct)

17 / 40

What is the primary difference between R-CNN and YOLO in object detection?

YOLO predicts bounding boxes in one pass

R-CNN processes regions sequentially (correct)

R-CNN uses anchor boxes

18 / 40

What is the primary use of data augmentation in training object detection models?

Increasing model robustness (correct)

Enhancing inference speed

Reducing model complexity

19 / 40

Which object detection algorithm uses a single neural network to predict bounding boxes and class probabilities?

R-CNN (Region-based Convolutional Neural Network)

SSD (Single Shot MultiBox Detector)

YOLO (You Only Look Once) (correct)

20 / 40

What is the primary difference between object detection and object recognition?

Object detection localizes and classifies objects (correct)

Object detection enhances image quality

Object recognition identifies objects

21 / 40

Which algorithm is used for feature extraction in the R-CNN family of object detectors?

Region Proposal Network (RPN) (correct)

Selective Search

YOLO

22 / 40

What is the primary advantage of using deep learning for object detection over traditional methods?

Faster computation

End-to-end learning (correct)

Higher precision

23 / 40

What is the primary advantage of using anchor-free object detection methods?

Higher accuracy

Flexibility in object scale and aspect ratio (correct)

Faster inference time

24 / 40

Which algorithm is known for its speed and efficiency in real-time object detection?

Faster R-CNN

Mask R-CNN

EfficientDet (correct)

25 / 40

Which technique uses bounding boxes to localize objects in images?

Object Segmentation

Object Classification

Object Localization (correct)

26 / 40

What does R-CNN stand for in object detection?

Region-based Convolutional Neural Network (correct)

Randomized Convolutional Network

Recursive Convolutional Network

27 / 40

Which evaluation metric penalizes false positives more severely than false negatives?

Recall (correct)

F1 score

Precision

28 / 40

What does COCO stand for in the context of object detection datasets?

Comprehensive Object Collection

Common Objects in Context (correct)

Contextual Object Collection

29 / 40

Which technique is used for handling class imbalance in object detection datasets?

Softmax Regression

Focal Loss (correct)

Dropout

30 / 40

Which technique is used for improving the accuracy of object detection models by refining bounding box coordinates?

Non-Maximum Suppression (NMS)

Bounding Box Regression (correct)

Anchor Box Adjustment

31 / 40

What does SSD stand for in the context of object detection?

Single Shot MultiBox Detector (correct)

Selective Search Detector

Super Scale Detection

32 / 40

What is the primary limitation of YOLO in detecting small objects?

Limited GPU memory

Higher computational cost

Lower spatial resolution (correct)

33 / 40

What is the purpose of anchor boxes in object detection models?

Enhancing feature extraction

Adjusting image brightness

Defining the aspect ratio and scale of objects (correct)

34 / 40

What does mAP measure in the context of object detection evaluation?

Maximum Accuracy Point

Mean Average Precision (correct)

Minimum Adjustment Parameter

35 / 40

What is object detection in computer vision?

Identifying and locating objects in images (correct)

Enhancing image quality

Classifying images

36 / 40

Which deep learning framework is commonly used for object detection tasks?

TensorFlow (correct)

Keras

PyTorch

37 / 40

Which algorithm is used for text detection in natural scene images?

EAST (Efficient and Accurate Scene Text Detector) (correct)

SSD

YOLO

38 / 40

Which algorithm is used for object detection with a focus on real-time performance?

Faster R-CNN

YOLO (You Only Look Once) (correct)

Mask R-CNN

39 / 40

What is the primary benefit of using transfer learning in object detection tasks?

Reducing training time

Leveraging pre-trained models for improved performance (correct)

Enhancing dataset diversity

40 / 40

Which technique is used for improving object detection accuracy by combining predictions from multiple models?

Adversarial Training

Reinforcement Learning

Ensemble Learning (correct)

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Computer MCQs 360April 11, 2024

0 20 1 minute read