Learn about Convolutional Neural Networks (CNNs), their components, and how they process visual data through convolution, pooling, and more.
AI systems reinforce what they have already learned, meaning that these algorithms are highly dependent on the data they are trained on. Because a human being selects that training data, the potential forbiasis inherent and must be monitored closely...
Theactivation layeris a commonly added and equally important layer in a CNN. The activation layer enables nonlinearity -- meaning the network can learn more complex (nonlinear) patterns. This is crucial for solving complex tasks. This layer often comes after the convolutional or fully connected lay...
Grieve notes that while ML is complicated, “at the end of the day, [ML] serves the same mechanical function that a flashlight, car, or computer screen does”29and that ML can be interpreted as meaning “[a device continually] performs a function with the data given to it and gets prog...
of a convolutional neural net and a transformer—excel at image recognition in near real-time. This tech is used today for things like robot search and rescue or assistive image and text recognition, as well as the much more controversial practice of dragnet facial recognition, à la Hong ...
Margaret is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles by the...
Those smart machines are also getting faster and more complex. Some computers have now crossed theexascalethreshold, meaning they can perform as many calculations in a single second as an individual could in31,688,765,000 years. And beyond computation, which machines have long been faster at tha...
What is the difference between AI and ML? Artificial intelligence (AI) is a broad field that refers to the ability of a machine to complete tasks that typically require human intelligence. Machine learning (ML) is a subfield of artificial intelligence that specifically refers to machines that can...
These embeddings are generated using convolutional neural networks (CNNs) like ResNet or Vision Transformers (ViT). They power applications like image search (e.g., Google Lens) and object detection. Word embeddings: Vector representations of words that capture semantic meaning and contextual ...
In some scenarios, the embedding process is an integrated part of a larger neural network. For example, in the encoder-decoderconvolutional neural networks (CNNs)used for tasks such asimage segmentation, the act of optimizing the entire network to make accurate predictions entails training the enco...