Question
I have the following input and target matrix Input: 110 samples of 273x262 Target: 110 samples of 273x262 I have to work on deep learning regression problem with a simple layers as shown below Layer: [imageInputLayer() convolution2dLayer(5,16,'Padding','same') batchNormalizationLayer reluLayer fullyConnectedLayer() regressionLayer] What is the matrix size I have to use for the inputlayer and fullyconnectedlayer? I am thinking of 4D matrix of size [273, 262, 1, 110] for inputlayer and a 2D matrix of size [273*263, 110] for output layer. Is this correct? Will this exceed the matrix array size preference? Any other suggestions.
Expert Answer
Prashant Kumar
PhD Expert
Answered Aug 23, 2026
From my understanding, you are working with grayscale images on a deep learning regression model. You are expecting a output in the form of a matrix for each image and not a single valued scalar output.
For imageInputLayer, size of the input data is specified as a row vector of integers [h w c], where h, w, and c correspond to the height, width, and number of channels respectively. You do not need to specify the number of samples. Hence, as per my understanding, the inputSize should be a row vector [273, 262, 1].
For fullyConnectedLayer, output size must be a positive integer. You shall not specify the sample size here as well. Hence as per my understanding, the outputSize should be 273*262.
100% Run Guarantee
3-Hour Fast-Track Delivery
Need a Custom Version or Complete Simulation for This Problem?
Our 500+ PhD engineers build, debug, and optimize working MATLAB scripts and Simulink (.slx) models tailored to your exact assignment rubrics with zero plagiarism.
Tested on MATLAB R2024b / R2026a
Turnitin 0% Plagiarism Report
Free 7-Day Revisions Guarantee
Have a different question? Ask here
Related deep learning Questions & Solutions
Browse All →
Explore similar technical troubleshooting questions and verified MATLAB solutions:
Ready-to-Run MATLAB & Simulink Projects
Browse All Projects →