Results 51 to 60 of about 82,326 (277)
Unsupervised adaptation of PLDA models for broadcast diarization
EURASIP Journal on Audio, Speech, and Music Processing, 2019 We present a novel model adaptation approach to deal with data variability for speaker diarization in a broadcast environment. Expensive human annotated data can be used to mitigate the domain mismatch by means of supervised model adaptation approaches ...
Ignacio Viñals +4 more
doaj +1 more source
EQAdap: Equipollent Domain Adaptation Approach to Image Deblurring
IEEE Access, 2022 In this paper, we present an end-to-end unsupervised domain adaptation approach to image deblurring. This work focuses on learning and generalizing the complex latent space of the source domain and transferring the extracted information to the unlabeled ...
Ibsa Jalata +5 more
doaj +1 more source
Adversarial Discriminative Domain Adaptation
, 2017 Adversarial learning methods are a promising approach to training robust deep networks, and can generate complex samples across diverse domains. They also can improve recognition despite the presence of domain shift or dataset bias: several adversarial ...
Darrell, Trevor +3 more
core +1 more source
A Domain Agnostic Normalization Layer for Unsupervised Adversarial Domain Adaptation
, 2018 We propose a normalization layer for unsupervised domain adaption in semantic scene segmentation. Normalization layers are known to improve convergence and generalization and are part of many state-of-the-art fully-convolutional neural networks.
Dubbelman, Gijs +2 more
core +1 more source
Molecular Oncology, EarlyView.Adaptaquin selectively kills glioma stem cells while sparing differentiated brain cells. Transcriptomic and proteomic analyses show Adaptaquin disrupts iron and cholesterol homeostasis, with iron chelation amplifying cytotoxicity via cholesterol depletion, mitochondrial dysfunction, and elevated reactive oxygen species.
Adrien M. Vaquié +16 more
wiley +1 more source
Molecular Oncology, EarlyView.Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice +16 more
wiley +1 more source
Unsupervised Transductive Domain Adaptation
, 2016 Supervised learning with large scale labeled datasets and deep layered models has made a paradigm shift in diverse areas in learning and recognition. However, this approach still suffers generalization issues under the presence of a domain shift between the training and the test data distribution.
Sener, Ozan +3 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.The study proposes a 1‐bit programmable metasurface based on flip‐disc display, named flip‐disc metasurface (FD‐MTS). This new design enables ultralow energy consumption while maintaining coding patterns. It also exhibits high scalability and multifunctional flexibility.
Jiang Han Bao +8 more
wiley +1 more source
Advanced Functional Materials, EarlyView.This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee +17 more
wiley +1 more source
SFDA-CD: A Source-Free Unsupervised Domain Adaptation for VHR Image Change Detection
Remote SensingDeep models may have disappointing performance in real applications due to the domain shifts in data distributions between the source and target domain. Although a few unsupervised domain adaptation methods have been proposed to make the pre-train models
Jingxuan Wang, Chen Wu
doaj +1 more source