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Video has a temporal dimension that makes a TDNN an ideal solution to analysing motion patterns. An example of this analysis is a combination of vehicle detection and recognizing pedestrians. [ 15 ] When examining videos, subsequent images are fed into the TDNN as input where each image is the next frame in the video.
[3] [4] In 2024, a 113 billion-parameter ViT model was proposed (the largest ViT to date) for weather and climate prediction, and trained on the Frontier supercomputer with a throughput of 1.6 exaFLOPs. [5] Subsequent to its publication, many variants were proposed, with hybrid architectures with both features of ViTs and CNNs.
The SSIM index is a full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as reference. SSIM is a perception -based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual ...
Kernel functions have been introduced for sequence data, graphs, text, images, as well as vectors. Algorithms capable of operating with kernels include the kernel perceptron , support-vector machines (SVM), Gaussian processes , principal components analysis (PCA), canonical correlation analysis , ridge regression , spectral clustering , linear ...
In early studies, ESNs were shown to perform well on time series prediction tasks from synthetic datasets. [ 1 ] [ 17 ] Today, many of the problems that made RNNs slow and error-prone have been addressed with the advent of autodifferentiation (deep learning) libraries, as well as more stable architectures such as long short-term memory and ...
Video super-resolution (VSR) is the process of generating high-resolution video frames from the given low-resolution video frames. Unlike single-image super-resolution (SISR) , the main goal is not only to restore more fine details while saving coarse ones, but also to preserve motion consistency.
The following is a simplistic illustrated explanation of how motion compensation works. Two successive frames were captured from the movie Elephants Dream.As can be seen from the images, the bottom (motion compensated) difference between two frames contains significantly less detail than the prior images, and thus compresses much better than the rest.
Connected-component labeling (CCL), connected-component analysis (CCA), blob extraction, region labeling, blob discovery, or region extraction is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic.