Glossary

Searchable terminology from accessibility, web standards, and related fields.

4 results found in Deep Learning.

Attention Mechanism (Attention)
A technique in neural networks that allows models to focus on relevant parts of the input when generating each part of the output, rather than relying solely on a fixed-length context vector. In seque…
Inception-v3 (Inception v3)
A deep convolutional neural network architecture developed by Google for image recognition, introduced in 2015. It uses "inception modules" that apply multiple convolution filter sizes in parallel to …
Sequence-to-Sequence (Seq2Seq, Encoder-Decoder)
A neural network architecture designed for tasks where both input and output are sequences of variable length, such as machine translation, speech recognition, and video captioning. A seq2seq model co…
Transformer (Transformer Model, Transformer Architecture)
A deep learning architecture introduced by Vaswani et al. in 2017 that relies entirely on attention mechanisms rather than recurrence (RNNs) or convolution for sequence modeling tasks. Transformers pr…