Zobrazeno 1 - 10
of 10 070
pro vyhledávání: '"Hu, Jie"'
Semi-Supervised Instance Segmentation (SSIS) aims to leverage an amount of unlabeled data during training. Previous frameworks primarily utilized the RGB information of unlabeled images to generate pseudo-labels. However, such a mechanism often intro
Externí odkaz:
http://arxiv.org/abs/2406.17413
Autor:
Chen, Yirui, Huang, Xudong, Zhang, Quan, Li, Wei, Zhu, Mingjian, Yan, Qiangyu, Li, Simiao, Chen, Hanting, Hu, Hailin, Yang, Jie, Liu, Wei, Hu, Jie
The extraordinary ability of generative models emerges as a new trend in image editing and generating realistic images, posing a serious threat to the trustworthiness of multimedia data and driving the research of image manipulation detection and loc
Externí odkaz:
http://arxiv.org/abs/2406.16531
Autor:
Hu, Jie, Boussaha, Faouzi, Nicaise, Paul, Chaumont, Christine, Appavou, Maria, Pham, Viet Dung, Piat, Michel
Publikováno v:
Appl. Phys. Lett. 124, 242602 (2024)
In this paper, we investigate the single photon response from the reflection of the Microwave Kinetic Inductance Detector (MKID) array. Reflection measurements are carried out using two configurations: one is measured simultaneously with the transmis
Externí odkaz:
http://arxiv.org/abs/2406.09436
Autor:
Zhang, Zhan, Zhang, Qin, Jiao, Yang, Lu, Lin, Ma, Lin, Liu, Aihua, Liu, Xiao, Zhao, Juan, Xue, Yajun, Wei, Bing, Zhang, Mingxia, Gao, Ru, Zhao, Hong, Lu, Jie, Li, Fan, Zhang, Yang, Wang, Yiming, Zhang, Lei, Tian, Fengwei, Hu, Jie, Gou, Xin
Publikováno v:
Artificaial Intelligence Review, (2024) 57:151
AI-aided clinical diagnosis is desired in medical care. Existing deep learning models lack explainability and mainly focus on image analysis. The recently developed Dynamic Uncertain Causality Graph (DUCG) approach is causality-driven, explainable, a
Externí odkaz:
http://arxiv.org/abs/2406.05746
In order to transmit data and transfer energy to the low-power Internet of Things (IoT) devices, integrated data and energy networking (IDEN) system may be harnessed. In this context, we propose a bitwise end-to-end design for polar coded IDEN system
Externí odkaz:
http://arxiv.org/abs/2406.04721
Stochastic bilevel optimization tackles challenges involving nested optimization structures. Its fast-growing scale nowadays necessitates efficient distributed algorithms. In conventional distributed bilevel methods, each worker must transmit full-di
Externí odkaz:
http://arxiv.org/abs/2405.18858
Recent semi-supervised object detection (SSOD) has achieved remarkable progress by leveraging unlabeled data for training. Mainstream SSOD methods rely on Consistency Regularization methods and Exponential Moving Average (EMA), which form a cyclic da
Externí odkaz:
http://arxiv.org/abs/2405.13374
Quantifying the size of cell populations is crucial for understanding biological processes such as growth, injury repair, and disease progression. Often, experimental data offer information in the form of relative frequencies of distinct cell types,
Externí odkaz:
http://arxiv.org/abs/2405.04557
Autor:
Appavou, Maria, Ribeiro, Lucas, Nicaise, Paul, Hu, Jie, Martin, Jean-Marc, Firminy, Josiane, Chaumont, Christine, Bonifacio, Piercarlo, Boussaha, Faouzi
We report on simulations of a novel design of optical titanium nitride (TiN)- based Kinetic Inductance Detectors (KIDs) in order to improve their response to optical photons. We propose to separate the meander from the substrate to trap hot phonons g
Externí odkaz:
http://arxiv.org/abs/2405.02837
Diffusion Transformers (DiTs) introduce the transformer architecture to diffusion tasks for latent-space image generation. With an isotropic architecture that chains a series of transformer blocks, DiTs demonstrate competitive performance and good sc
Externí odkaz:
http://arxiv.org/abs/2405.02730