Titlebook: Neural Information Processing; 29th International C Mohammad Tanveer,Sonali Agarwal,Adam Jatowt Conference proceedings 2023 The Editor(s) (

Noctambulant

多嘴

Fibrillation

Multi-level Network Based on Text Attention and Pose-Guided for Person Re-IDerson is known. Since there is vast modal difference between the image and text, how to effectively match the semantic features of the image-text is extremely important. Existing schemes mainly consider how to extract more accurate text representation or more complete image representation but ignore

Invigorate

Sketch Image Style Transfer Based on Sketch Density Controllingering the original sketch contents. Previous methods generally disentangle the content and style of reference image and transfer the style to sketch image. However, the textures or the painting strokes of the reference art image could be a part of content as well as style. It is difficult to decide

frivolous

VAE-AD: Unsupervised Variational Autoencoder for Anomaly Detection in Hyperspectral ImagesIn this paper, we proposed a lightweight Variational Autoencoder anomaly detector (VAE-AD) for hyperspectral data. VAE is used to learn the background distribution of the image, and thereafter it is used to construct a background representation for each pixel. Further reconstruction error is calcula

FLINT

女上瘾

Frequency-Range

冒号

可憎

A Multi-modal Graph Convolutional Network for Predicting Human Breast Cancer Prognosisancer is crucial. If breast cancer prognosis predictions were correct, a substantial number of people may be spared from unnecessary adjuvant systemic treatment and the enormous medical costs. Several studies have already been conducted to accomplish this. But, most studies employ specific gene expr