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Punched tape with the word "Wikipedia" encoded in ASCII.Presence and absence of a hole represents 1 and 0, respectively; for example, "W" is encoded as "1010111". Character encoding is the process of assigning numbers to graphical characters, especially the written characters of human language, allowing them to be stored, transmitted, and transformed using digital computers. [1]
This is a list of dictionaries considered authoritative or complete by approximate number of total words, or headwords, included. Figures do not take account of entries with senses for different word classes (such as noun and adjective) and homographs. Although it is possible to count the number of entries in a dictionary, it is not possible to ...
t. e. A standard Transformer architecture, showing on the left an encoder, and on the right a decoder. Note: it uses the pre-LN convention, which is different from the post-LN convention used in the original 2017 Transformer. A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention ...
List of English words with disputed usage. List of English–Spanish interlingual homographs. List of ethnic slurs. List of generic and genericized trademarks. List of Germanic and Latinate equivalents in English. List of self-contradicting words in English. Lists of Merriam-Webster's Words of the Year. Most common words in English.
In the process of encoding, the sender (i.e. encoder) uses verbal (e.g. words, signs, images, video) and non-verbal (e.g. body language, hand gestures, face expressions) symbols for which he or she believes the receiver (that is, the decoder) will understand. The symbols can be words and numbers, images, face expressions, signals and/or actions.
e. An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data ( unsupervised learning ). [ 1][ 2] An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.
Semantic encoding is the processing and encoding of sensory input that has particular meaning or can be applied to a context. Various strategies can be applied such as chunking and mnemonics to aid in encoding, and in some cases, allow deep processing, and optimizing retrieval.
The encoder is usually a simple circuit which has state memory and some feedback logic, normally XOR gates. The decoder can be implemented in software or firmware. The Viterbi algorithm is the optimum algorithm used to decode convolutional codes.