filtering

ing and neural networks is still in its infancy. Promising avenues include: Deep Kalman Filters: Combining deep learning with probabilistic filtering to handle complex, nonlinear systems. Neuro-symbolic Hybrid Models: Embedding filtering mechanisms wit

convolved_img = conv2(double(gray_img), kernel, 'same'); % Display result figure; imshow(mat2gray(convolved_img)); title('Laplacian Filter via conv2'); ``` Practical Tips for Effective Image Filtering in MATLAB