Quiz on Human Activity Recognition Using Deep Learning

What is the main focus of the proposed framework in the paper?

• Speech recognition

• Natural language processing

• Human activity recognition

• Image recognition

Which type of neural network is primarily used in the proposed model?

• Recurrent Neural Network (RNN)

• Convolutional Neural Network (CNN)

• Generative Adversarial Network (GAN)

• Radial Basis Function Network (RBFN)

What mechanism is incorporated into the CNN model to enhance feature representation?

• Dropout mechanism

• Attention mechanism

• Pooling mechanism

• Normalization mechanism

What type of data is primarily used for human activity recognition in this study?

• Text data

• Image data

• Sensor data

• Audio data

Which datasets were used to evaluate the proposed model?

• Fashion-MNIST and SVHN

• MNIST and CIFAR-10

• WISDM and UCI HAR

• ImageNet and COCO

What is the purpose of the squeeze-and-excitation module in the model?

• To reduce the number of parameters

• To improve training speed

• To enhance feature recalibration

• To increase the model's depth

What is a significant challenge faced by the HAR community mentioned in the paper?

• Scarcity of labeled training samples

• Simplicity of feature extraction

• High availability of labeled data

• Low computational cost

What type of attention mechanism is used in the proposed framework?

• Spatial attention

• Temporal attention

• Squeeze-and-excitation attention

• Multi-head attention

What is the reported accuracy of the proposed model on the WISDM dataset?

• 0.964

• 0.9818

• 0.9538

• 0.947

How many convolutional heads are used in the proposed multi-head model?

• One

• Two

• Three

• Four