MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
Mitchell traces the evolution of AI from Alan Turing’s early ideas to modern systems. The book explores language, images, and ...
Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...
Abstract: In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing. The success of ...
Abstract: The computational complexity of the Transformer model grows quadratically with input sequence length. This causes a sharp increase in computational cost and memory consumption for ...
Abstract: Image steganography conceals secret data within a cover image to generate a new image (stego image) in a manner that makes the secret data undetectable. The main problem in image ...
Abstract: As computer vision and AI technologies advance at an accelerated pace, image processing has permeated critical domains like healthcare diagnostics, surveillance systems, and autonomous ...
Abstract: Multidimensional parameter estimation is a critical challenge in fields such as radar, sonar, and wireless communications, where the space-alternating generalized expectation-maximization ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
This article appears in the December 2025 issue of The American Prospect magazine. Subscribe here. Earlier this year, a slightly balding man in spectacles, a black T-shirt, and bright high-top ...
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