Results 151 to 160 of about 133,828 (342)
Computation of discrete cosine transform using Clenshaw\u27s recurence formula
, 1995 Clenshaw’s recurrenee formula is used to derive recursive algorithms for the discrete cosine transform @CT) and the inverse discrete cosine transform (IDCT).
Aburdene, Maurice F. +2 more
core
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Using Discrete Cosine Transform Based Features for Human Action Recognition
, 2020 -Recognizing human action in complex video sequences has always been challenging for researchers due to articulated movements, occlusion, background clutter, and illumination variation.
Tasweer Ahmad +3 more
core
Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
Normal bases expansion of the discrete cosine transform
, 2020 [[abstract]]In this correspondence, we show that the discrete cosine transform (DCT) can be obtained by projecting the discrete Fourier transform from the extension field to the basefield, Applying the framework of projection operator, a fast fully ...
吳家麟, Wu, JL
core
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
Advanced Intelligent Discovery, EarlyView.The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
, 2011 PERANCANGAN PROGRAM APLIKASI PENGURANGAN DUPLIKASI FILE MUSIK DENGAN METODE INVERSE MODIFIED DISCRETE COSINE TRANSFORM - IMDCT (Inverse Modified Discrete Cosine Transform), perbandingan mp3, duplikasi file ...
XAVERIUS FERRYADI, FRANSISKUS
core
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Advanced Intelligent Discovery, EarlyView.Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source