Object Detection and Recognition MCQs With Answers

Computer MCQs 360April 11, 2024

0 50 1 minute read

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 technique combines object detection and image segmentation?

YOLO (You Only Look Once)

Mask R-CNN (correct)

Faster R-CNN

2 / 40

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

Comprehensive Object Collection

Common Objects in Context (correct)

Contextual Object Collection

3 / 40

What does SSD stand for in object detection?

Single Shot MultiBox Detector (correct)

Scale-Space Detection

Selective Search Detector

4 / 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)

5 / 40

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

Mask R-CNN

YOLO (You Only Look Once) (correct)

Faster R-CNN

6 / 40

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

Object detection localizes and classifies objects (correct)

Object recognition identifies objects

Object detection enhances image quality

7 / 40

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

SSD

Mask R-CNN (correct)

YOLO

8 / 40

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

R-CNN (Region-based Convolutional Neural Network)

YOLO (You Only Look Once) (correct)

SSD (Single Shot MultiBox Detector)

9 / 40

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

YOLO

SSD

Faster R-CNN (correct)

10 / 40

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

RetinaNet (correct)

SSD

YOLO

11 / 40

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

K-Means Clustering

Gaussian Mixture Model

Selective Search (correct)

12 / 40

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

Limited GPU memory

Lower spatial resolution (correct)

Higher computational cost

13 / 40

Which feature descriptor is used in traditional object detection algorithms?

Scale-Invariant Feature Transform (SIFT)

Speeded-Up Robust Features (SURF)

Histogram of Oriented Gradients (HOG) (correct)

14 / 40

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

Enhancing inference speed

Reducing model complexity

Increasing model robustness (correct)

15 / 40

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

Augmenting training data

Enhancing image resolution

Removing duplicate detections (correct)

16 / 40

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

Focal Loss (correct)

Softmax Regression

Dropout

17 / 40

What does IoU stand for in object detection evaluation metrics?

Index of Utility

Input over Unit

Intersection over Union (correct)

18 / 40

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

Mask R-CNN

Faster R-CNN

EfficientDet (correct)

19 / 40

What is object detection in computer vision?

Enhancing image quality

Identifying and locating objects in images (correct)

Classifying images

20 / 40

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

Minimum Adjustment Parameter

Maximum Accuracy Point

Mean Average Precision (correct)

21 / 40

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

Extracting fixed-size features from RoIs (correct)

Enhancing object recognition

Adjusting anchor box sizes

22 / 40

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

Bounding Box Regression (correct)

Non-Maximum Suppression (NMS)

Anchor Box Adjustment

23 / 40

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

Low image resolution

Overlapping objects (correct)

Limited computing resources

24 / 40

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

MobileNet (correct)

ResNet

VGGNet

25 / 40

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

SSD

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

YOLO

26 / 40

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

Keras

PyTorch

TensorFlow (correct)

27 / 40

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

Lower memory usage

Higher accuracy

Simplicity in implementation (correct)

28 / 40

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

Selective Search

Region Proposal Network (RPN) (correct)

YOLO

29 / 40

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

R-CNN uses anchor boxes

YOLO predicts bounding boxes in one pass

R-CNN processes regions sequentially (correct)

30 / 40

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

Faster computation

Higher precision

End-to-end learning (correct)

31 / 40

What does FPN stand for in object detection architectures?

Fast Processing Network

Feature Pyramid Network (correct)

Feature Propagation Network

32 / 40

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

Reinforcement Learning

Ensemble Learning (correct)

Adversarial Training

33 / 40

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

Flexibility in object scale and aspect ratio (correct)

Faster inference time

Higher accuracy

34 / 40

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

Defining grid cells for object localization (correct)

Adjusting object size

Enhancing image resolution

35 / 40

Which evaluation metric measures the accuracy of object detection algorithms?

Error Margin

Accuracy Rate

mAP (mean Average Precision) (correct)

36 / 40

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

Recall (correct)

F1 score

Precision

37 / 40

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

Reducing training time

Enhancing dataset diversity

Leveraging pre-trained models for improved performance (correct)

38 / 40

Which technique uses bounding boxes to localize objects in images?

Object Localization (correct)

Object Classification

Object Segmentation

39 / 40

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

Selective Search Detector

Super Scale Detection

Single Shot MultiBox Detector (correct)

40 / 40

What does R-CNN stand for in object detection?

Region-based Convolutional Neural Network (correct)

Randomized Convolutional Network

Recursive Convolutional Network

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Computer MCQs 360April 11, 2024

0 50 1 minute read