Results 71 to 80 of about 113,519 (298)
Learning Binary Residual Representations for Domain-specific Video Streaming
, 2017 We study domain-specific video streaming. Specifically, we target a streaming setting where the videos to be streamed from a server to a client are all in the same domain and they have to be compressed to a small size for low-latency transmission ...
Kautz, Jan +4 more
core +1 more source
Advanced Science, EarlyView.SAGE is a unified framework for spatial domain identification in spatial transcriptomics that jointly models tissue architecture and gene programs. Topic‐driven gene selection (NMF plus classifier‐based scoring) highlights spatially informative genes, while dual‐view graph embedding fuses local expression and non‐local functional relations.
Yi He +5 more
wiley +1 more source
Advanced Science, EarlyView.This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang +3 more
wiley +1 more source
Analysis of Multiscale Condensation Phenomena Using a Zero‐Shot Computer Vision Framework
Advanced Science, EarlyView.A zero‐shot computer vision framework quantifies multiscale condensation dynamics by automatically segmenting droplets and extracting physical parameters without labeled data. The workflow integrates data mining and statistical analysis to reveal droplet growth, coalescence statistics, and sweeping behaviors, enabling label‐free measurement of heat ...
Donghyeong Lee +5 more
wiley +1 more source
IEEE AccessA fault detection method for power conversion circuits using thermal images and a convolutional autoencoder is presented. The autoencoder is trained on thermal images captured from a commercial power module at randomly varied load currents and augmented ...
Noboru Katayama, Rintaro Ishida
doaj +1 more source
Automatic Detection of Phonological Errors in Child Speech Using Siamese Recurrent Autoencoder [PDF]
, 2020 Si-Ioi Ng, Tan Lee
openalex +1 more source
Autoencoding any Data through Kernel Autoencoders
, 2018 This paper investigates a novel algorithmic approach to data representation based on kernel methods. Assuming that the observations lie in a Hilbert space X, the introduced Kernel Autoencoder (KAE) is the composition of mappings from vector-valued Reproducing Kernel Hilbert Spaces (vv-RKHSs) that minimizes the expected reconstruction error.
Laforgue, Pierre +2 more
openaire +2 more sources
Advanced Electronic Materials, EarlyView.This work proposed an unsupervised physics‐informed deep learning method of generating space‐time‐coding metasurface coding patterns for arbitrary single‐ and dual‐beam requirements at each harmonic. This method is specially designed for the coding pattern design task of multi‐bit scenario, and it can effectively handle the optimization trouble caused ...
Jiang Han Bao +6 more
wiley +1 more source
Generative Artificial Intelligence Shaping the Future of Agri‐Food Innovation
AgriFood: Journal of Agricultural Products for Food, EarlyView.Emerging use cases of generative artificial intelligence in agri‐food innovation. ABSTRACT The recent surge in generative artificial intelligence (AI), typified by models such as GPT, diffusion models, and large vision‐language architectures, has begun to influence the agri‐food sector.
Jun‐Li Xu +2 more
wiley +1 more source
The Astronomical JournalWe present a novel method for anomaly detection in solar system object data in preparation for the Legacy Survey of Space and Time. We train a deep autoencoder for anomaly detection and use the learned latent space to search for other interesting objects.
Brian Rogers +4 more
doaj +1 more source