How can face recognition algorithms surpass humans in matchi…
How can face recognition algorithms surpass humans in matching faces over changes in illumination? A. By using color filters that mimic human eye perception under low lightB. By enhancing sharpness through contrast adjustment in every imageC. By learning invariant features using deep neural networks trained on varied lighting conditionsD. By converting all face images into grayscale to remove lighting differences entirely
Read DetailsWhat are the deep learning optimization challenges? A. Exces…
What are the deep learning optimization challenges? A. Excessive memory usage due to shallow architectures and simple data formatsB. Getting stuck in local minima or saddle points during the training processC. Underfitting caused by applying too many optimization algorithms at onceD. Overflow errors resulting from storing gradients in fixed-length character arrays
Read DetailsHow does a Recursive Neural Network (RvNN) process input in…
How does a Recursive Neural Network (RvNN) process input in a hierarchical or tree-like structure? A. It scans the input linearly from left to right and encodes each element using a time-based memory mechanism to retain context.B. It processes each node independently and combines all representations at the final output layer for prediction or classification.C. It combines child node representations recursively using shared weights to build parent nodes until a root representation is formed.D. It breaks the input into equal-sized segments, processes them in parallel, and then merges the results through attention layers at the end.
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