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Which of the following best describes the characteristics of the ReLU activation function?
①The output is always limited to the range from 0 to 1.
②The output increases exponentially for negative inputs.
③It is a simple nonlinear function that returns 0 when the input is negative and returns the input value when it is positive.
④Because it is always differentiable, it completely solves the vanishing gradient problem.
⑤An activation function specific to convolutional layers and not used in fully connected layers.