Object Detection
Object detection is a computer technology related to computer vision and image processing that offers the capability of identifying instances of semantic objects of specific
Category: Lexicon
Object Tracking
Object tracking is a concept employed within Artificial Intelligence which involves locating and following one or multiple specific objects over a video sequence or set
Obsorve
Obsorve is a combination of the words “Observe” and “Absorb.” It denotes a learning technique by observing first and then absorbing the information – in
Opporture
The word Opporture was coined out of a combination of the words opportunity and future. Opporture, an AI company, stands for creating opportunities for the
Panoptic Segmentation
In computer vision, the task of panoptic segmentation involves three distinct steps: separation of each object in an image into individual parts that are independent
Part-of-Speech Tagging
Part-of-Speech (POS) tagging is a crucial step in natural language processing (NLP) and computational linguistics. It involves figuring out and assigning parts of speech, like
Pixel Learning
A pixel is the smallest unit of display on a digital device that shows a picture or an image. Any digital image, video or object
Polygon Annotation
Polygon annotation is a precise and accurate process used to define the boundaries of an object or region in an image or video. It involves
Q-function
In artificial intelligence, the Q-function (short for Quality function) maps a state-action pair to a numerical value, which represents the expected total reward that an
Q-learning
Q-Learning is a model-free, off-policy Reinforcement learning approach that determines the optimal course of action when presented with a given environment. This action is selected
Recall (Sensitivity)
Recall refers to the ability of a machine learning model to identify relevant instances of a particular class or category accurately. More specifically, it is
Recurrent Neural Networks (RNNs)
Recurrent neural networks, or RNNs, are a category of artificial neural networks. They are characterized by the flow of data in multiple directions between layers.
