Search Results
5 results for “deep-learning”
Attention Mechanism
A neural network technique that enables models to dynamically weight the relevance of different parts of an input sequence when producing each output element, forming the core of transformer architectures.
Autoencoder
An autoencoder is a type of artificial neural network trained to reconstruct its input through a compressed internal representation, used for dimensionality reduction, feature learning, and anomaly detection.
Image Segmentation
A computer vision task that partitions an image into meaningful regions by assigning a class label to every pixel, enabling pixel-level understanding of visual scenes.
Long Short-Term Memory (LSTM)
Long Short-Term Memory is a recurrent neural network architecture designed to learn long-range dependencies in sequential data by using gating mechanisms to control information flow.
Optical Character Recognition
A computer vision technology that converts images of typed, handwritten, or printed text into machine-readable digital text, increasingly powered by deep learning and transformer-based vision models.