<prompt> Hlalosa sepheo sa li-CNN ponong ea khomphutha.nan  <response>: Instruction in English: Explain the purpose of CNNs in computer vision. . Response in English: CNNs, or Convolutional Neural Networks, are a type of neural network architecture commonly used in computer vision tasks, such as image recognition and classification. The main purpose of a CNN is to process and analyze image data in order to extract meaningful information and discern patterns. A CNN is designed to take in input images and apply a series of convolutional and pooling layers to reduce the spatial dimensions of the image while increasing the depth number of channels. This allows the network to learn the hierarchical features of the image, from low-level features such as edges and corners, to high-level features such as the shape and context of objects within the image. The CNN applies a series of filters to the image, each of which is trained to recognize a specific feature within the image. As the image passes through successive layers, the filters become more complex and specialized, allowing the network to recognize more abstract and sophisticated features. The final layers of the network are typically composed of fully connected layers, which produce the final output of the network, such as class probabilities for an image recognition task.In summary, the purpose of CNNs in computer vision is to provide a powerful tool for processing and analyzing visual data, allowing for the automatic identification and extraction of meaningful information from images. They are able to effectively learn and recognize patterns and features within images, making them an essential component in many computer vision systems. . Response in Sesotho: CNNs, kapa Convolutional Neural Networks, ke mofuta oa meralo ea neural network e sebelisoang hangata mesebetsing ea pono ea khomphutha, joalo ka ho lemoha litšoantšo le ho arola. Sepheo se seholo sa CNN ke ho sebetsa le ho sekaseka lintlha tsa litšoantšo e le ho ntša tlhahisoleseding e utloahalang le ho lemoha mekhoa. CNN e etselitsoe ho nka litšoantšo tse kenyang le ho sebelisa letoto la likarolo tsa convolutional le pooling ho fokotsa boholo ba sebaka sa setšoantšo ha e ntse e eketsa botebo palo ea likanale. Sena se lumella marang-rang ho ithuta likarolo tsa boemo bo phahameng ba setšoantšo, ho tloha likarolong tse tlaase tse kang mathōko le likhutlong, ho ea ho likarolo tse phahameng tse kang sebōpeho le moelelo oa lintho tse ka hara setšoantšo. CNN e sebelisa letoto la li-filters setšoantšong, se seng le se seng se koetliselitsoe ho lemoha tšobotsi e itseng ka hara setšoantšo. Ha setšoantšo se ntse se feta ka lihlopha tse latellanang, li-filters li fetoha tse rarahaneng le tse khethehileng, tse lumellang marang-rang ho lemoha likarolo tse sa bonahaleng le tse rarahaneng. Likarolo tsa ho qetela tsa marang-rang hangata li entsoe ka lihlopha tse kopantsoeng ka ho feletseng, tse hlahisang tlhahiso ea ho qetela ea marang-rang, joalo ka menyetla ea sehlopha bakeng sa mosebetsi oa ho lemoha setšoantšo. Ka bokhutšoanyane, sepheo sa li-CNN ponong ea khomphieutha ke ho fana ka sesebelisoa se matla sa ho sebetsana le ho hlahloba lintlha tse bonahalang, ho lumella ho tsebahatsa ka mokhoa o itekanetseng le ho ntša boitsebiso bo nang le moelelo litšoantšong. Ba khona ho ithuta ka katleho le ho lemoha mekhoa le likarolo ka hara litšoantšo, ho ba etsa karolo ea bohlokoa litsebetsong tse ngata tsa pono ea khomphutha. 