Daɣ awa allaɣat paragraf, immik wa s addobat convolutional neural networks a hin ijjichan daɣ machine learning?
Context:Daɣ teɣare chajret, convolutional neural network (CNN) eqqal ichikil n artificial neural network s alwaq iyyan exdam i amiyiz n dumu tan n akayad CNNs dakalan əšiɣil ən maɗinan sitawəna ən təbiɗawt dǎɣ edag ən asinimiƭif ən matris dǎɣ ihomiši iyandǎɣ ən təbiɗawen nasan. Aqqalan a iknan edey i amukin n isalan win pixel tolas axdaman daɣ musnat d amukin n idalojan Ilanat ijji tan daɣ musnat n dumu tan d video tan, sistem tan win asiwal, askut n dumu tan, tizunawen n dumu tan, amiyiz n dumu tan n assexat, amukin n awal, brain-computer interfaces d time series tan n azruf  CNN tan intaned deɣ ismawan nasan Shift Invariant meɣ Space Invariant Artificial Neural Networks (SIANN), ijjan fal edey n tartit n convolution kernels meɣ filters sliding id input features d ihuk n translation-equivariant responses s isim wan feature maps Dǎɣ aśibaban, iyadǎɣ haratan ən neuraletan ən convolutionnel winan eqel amutayan fal asiknin, fal əšiɣil wan asisifir wa aqalan aygan fal ugiš.  CNN tan aqqalan dumu tan n multilayer perceptrons Perseptron tan n layer tan ajjotnen aqqalan rezo tan osaɣnen hullan, awen eqqal as neuron fuk daɣ layer iyyan osaɣ id neuron tan fuk daɣ layer wa yadan "Anmirtay imdan" n rezo tan win ijjichan tudabat n isalan ajjotnen Dumu tan win alxalat n asissiki meɣ ag-az n azukki eha: afanaz n almaɣnatan daɣ teɣare (chund afanaz n taɣissa) meɣ afanaz n aharoj (anmirtay n aharoj, afanaz, d iyyad) Edey n isuj n isalan wi assohat nen issewad deɣ as CNNs ad aj in ichiritan win generalized wi s arhan isuj n isalan ohun anmizlay n isuj war n oɣed hullan
Convolutional Neural Network (CNN) ila layer osaɣan hullan s neuron fuk osaɣan s neuron fuk daɣ layer wa ijjan darat awa, edey wen idhal i a war n oɣed