Question 1
(a)
Explain the term : axon, cell body, synapse and dendrite
3 Marks
(b)
Explain the concept of perceptron with a neat diagram.
4 Marks
(c)
Explain different architectures of ANN with diagram.
7 Marks
Gujarat Technological UniversitySummer 2026 Examination
GTU 116AG01 Deep Learning and Neural Network Summer 2026 Paper Solution & PDF
B.E. · Computer Engineering · Semester 6 · Subject Code: 116AG01
Total Marks70 MarksExternal theory exam
Passing Marks23 Marks33% minimum cutoff
Exam Duration2.5 Hours10:30 AM – 1:00 PM
Paper Structure5 QuestionsWith internal OR choices
Question 2
(a)
Explain the concepts of overfitting and underfitting in neural network.
3 Marks
(b)
Compute the output of the following neural network model having (2, 2, 1) structure with linear activation function in the input layer and sigmoidal in the output layer, if the input vector is [1.2, 0.5], weight vectors are [0.04, 0.05; 0.2 0.02] and [0.06 0.15] respectively.
4 Marks
(c)
What is the role of activation functions in the context of neural network training? Explain any three activation function in details.
7 Marks
OR OPTION
(c)
(
i)Describe the concept of batch normalization.
ii)Explain the role of hyperparameter tuning in neural network.
7 Marks
Question 3
(a)
Define convolutional neural networks. Write the application of convolution operation.
3 Marks
(b)
How does pooling work? Explain with suitable example.
4 Marks
(c)
Draw and Explain architecture of CNN.
7 Marks
OR OPTION
(a)
Explain Stride and padding.
3 Marks
(b)
Explain convolutional operation and its advantages.
4 Marks
(c)
Briefly explain the two major steps namely Feature learning and Classification of CNN.
7 Marks
Question 4
(a)
Write advantages of recurrent neural network.
3 Marks
(b)
Explain types of RNN.
4 Marks
(c)
Draw and Explain architecture of RNN.
7 Marks
OR OPTION
(a)
What is the advanced use of recurrent neural network?
3 Marks
(b)
Write the difference between CNN and RNN.
4 Marks
(c)
Explain LSTM with diagram.
7 Marks
Question 5
(a)
Define Accuracy, Precision and Recall
3 Marks
(b)
Explain TensorFlow Architecture.
4 Marks
(c)
What is tensorflow? Explain types of tensor in detail.
7 Marks
OR OPTION
(a)
Define Tensor, Rank of Tensor and shape of Tensor
3 Marks
(b)
Write steps to train RNN.
4 Marks
(c)
What are the limitation of TensorFlow? Explain eager execution and graph execution mode in TensorFlow.
7 Marks
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About this Examination Paper & Attribution
Official Gujarat Technological University (GTU) examination paper and step-by-step solutions for Deep Learning and Neural Network (Summer 2026, B.E. · Computer Engineering, Sem 6). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.
Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.