I need a MATLAB source code to recognize different regular geometric shapes such as: squares,rectangles,triangles,circles and ellipses in different sizes using neural network. All of the images containing these shapes should be in binary format with the size of 300*400 pixels. would you please give me a MATLAB code to detect these geometric shapes?
4151A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalization, the output will be zero when and only when the input is: a) 000 or 110 or 011 or 101 b) 010 or 100 or 110 or 101 c) 000 or 010 or 110 or 100 d) 100 or 111 or 101 or 001
HCL,
1 7254A perceptron is: a) a single layer feed-forward neural network with pre-processing b) an auto-associative neural network c) a double layer auto-associative neural network d) a neural network that contains feedback
1 10060An auto-associative network is: a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing
1 17197A 4-input neuron has weights 1, 2, 3 and 4. The transfer function is linear with the constant of proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively. The output will be: a) 238 b) 76 c) 119 d) 123
1 10108Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None of the mentioned
1 5067Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned
1 14740What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) d) All of the mentioned
1 11736Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned
1 6354Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned
1 14320Neuro software is: a) A software used to analyze neurons b) It is powerful and easy neural network c) Designed to aid experts in real world d) It is software used by Neuro surgeon
2 8538Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.
1 7243What is back propagation? a) It is another name given to the curvy function in the perceptron b) It is the transmission of error back through the network to adjust the inputs c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn. d) None of the mentioned
1 7511. Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only class of problem that Perceptron can solve successfully c) Because they are the only mathematical functions that are continue d) Because they are the only mathematical functions you can draw
1 7974Post New AI Neural Networks Questions
What are batch, incremental, on-line, off-line, deterministic, stochastic, adaptive, instantaneous, pattern, constructive, and sequential learning?
What are neural networks? What are the types of neural networks?
What is simple artificial neuron?
Describe the structure of artificial neural networks?
Which is the similar operation performed by the drop-out in neural network?
What are artificial neural networks?
How to avoid overflow in the logistic function?
What are the applications of a Recurrent Neural Network (RNN)?
What are neural networks and how do they relate to ai?
How does an LSTM network work?
How are layers counted?
What can you do with an nn and what not?
What is a neural network and what are some advantages and disadvantages of such a network?
What is the role of activation functions in a Neural Network?
What is backprop?