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A: This question wants compression of Bytes Per Inch.
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A: The correct answer is d plot(t,y,'b-*.').
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A: Even numbers recognized by Least significant Bit (LSB). For explanation check below.
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A: Apply Playfair encoding rules on HU and find out the result. a. KS b.IV c.SK d.GY
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Q: cat(A,B); ut<<"A="<<A<<"\t"<<"B="<<B;
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Q: . The basic unit of computer storage is a. byte b. nibble c. bit d. word
A: Given that: The basic unit of computer storage is a. byte b. nibble c. bit d. word
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- 1. Consider an input image of shape 500x500x3. The image is flattened and a fully connected layer with 100 hidden units is used. What is the shape of the weight matrix of this layer (without the bias)? What is the shape of the bias? 2. You run this image in a convolutional layer with 10 filters, of kernel size 5x5. How many parameters does this layer have?MFC. Consider the following pixel filter: def clamp(pixel): new_r = max(75, min(100, pixel[0])) new_g = max(75, min(100, pixel[1])) new_b = max(75, min(100, pixel[2])) return [new_r, new_g, new_b] What does this do to an individual pixel? What would happen to an image if we used it to edit all the pixels? What would an image look like after it has been edited?The input image has been converted into a matrix of size 28 X 28 and a kernel/filter of size 3 X 3 with a stride of 2 and padding of 1. What will be the size of the convoluted matrix? A. 15 x 15 B. 14 x 14 C. 14 x 15 D. 14.5 x 14.5
- Describe an algorithm for converting a greyscale image to a two-bit image (i.e. only using black, dark grey, light grey and white), while preserving as much visual quality as possible. Your algorithm should map every input greyscale pixel to exactly one output pixel.A 3x3 kernel is sliding across an image (single channel image). At the current position the kernel stopped at a patch of pixels with the following values: 2 1 3 1 1 0 0 4 1 The kernel is defined as follows: 1 -1 1 0 2 0 1 -1 1 Compute the value that will go into the feature map for this convolution operation.Q2) Bilateral filter is a local and non-linear filter considers both gray level similarities and geometric closeness of the neighboring pixels without smoothing edges. It is used for removing Gaussian noise and defined as: BF[']P=WLP YgesGos (IIp — 4l]) Gor (IIp — Iq)) Iq Find the estimated value of the pixel 1(0,0) instead of its noisy value {I(0,0) =50} in image | which is defined below. Let: s = or = 1 100 100 100 90 100 120 110
- For an image of size 32x32 and a filter of size 5x5, if you want the convolution result to keep the original image size, what's the padding size in pixels? a) 5 b) 2 c)10 d) 3 explain.We have an input image of dimension 28X28X3. We want to use 5X5 filters to extract features. We need to extract 28X28X128 features. A) What will be the dimension of the filters, stride, and padding? B) How many multiplications do we need if we use just one CONV layer? C) How can we reduce the number of multiplicatoins needed? Show how? D) How much improvements can we get?Given the image below f(x,y), and the filter h(x,y), perform a convolution and calculate the new filtered pixel values for pixel c in the filtered image.
- Question 3 This is a question on Harris corner detection. Consider the Image (patch) I, shown as above. The numbers colored in red indicate the window, W. ii) Compute and show the Harris matrix (H) for W.When embedding a 10-bit message in an image using LSB replacement, write down the probability that the embedding will introduce k ∈ {0,1,...,10} embedding changes.Process the image given on the right by a 3x3 Laplacian filter (4-direction mask). Find the filter responses only when the center of the mask is within the shaded region to avoid the border effect (i.e. filtered image will have a size of 3x4 pixels). Why are the left and right parts of the filtered image so different?Suggest a procedure which maps the filtered image pixel values (including negative values) to integers in the range of [0, 255]to display the image on a monitor screen.