72 research outputs found
Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target Data
A recent study finds that existing few-shot learning methods, trained on the
source domain, fail to generalize to the novel target domain when a domain gap
is observed. This motivates the task of Cross-Domain Few-Shot Learning
(CD-FSL). In this paper, we realize that the labeled target data in CD-FSL has
not been leveraged in any way to help the learning process. Thus, we advocate
utilizing few labeled target data to guide the model learning. Technically, a
novel meta-FDMixup network is proposed. We tackle this problem mainly from two
aspects. Firstly, to utilize the source and the newly introduced target data of
two different class sets, a mixup module is re-proposed and integrated into the
meta-learning mechanism. Secondly, a novel disentangle module together with a
domain classifier is proposed to extract the disentangled domain-irrelevant and
domain-specific features. These two modules together enable our model to narrow
the domain gap thus generalizing well to the target datasets. Additionally, a
detailed feasibility and pilot study is conducted to reflect the intuitive
understanding of CD-FSL under our new setting. Experimental results show the
effectiveness of our new setting and the proposed method. Codes and models are
available at https://github.com/lovelyqian/Meta-FDMixup.Comment: Accepted by ACM Multimedia 202
On the Importance of Spatial Relations for Few-shot Action Recognition
Deep learning has achieved great success in video recognition, yet still
struggles to recognize novel actions when faced with only a few examples. To
tackle this challenge, few-shot action recognition methods have been proposed
to transfer knowledge from a source dataset to a novel target dataset with only
one or a few labeled videos. However, existing methods mainly focus on modeling
the temporal relations between the query and support videos while ignoring the
spatial relations. In this paper, we find that the spatial misalignment between
objects also occurs in videos, notably more common than the temporal
inconsistency. We are thus motivated to investigate the importance of spatial
relations and propose a more accurate few-shot action recognition method that
leverages both spatial and temporal information. Particularly, a novel Spatial
Alignment Cross Transformer (SA-CT) which learns to re-adjust the spatial
relations and incorporates the temporal information is contributed. Experiments
reveal that, even without using any temporal information, the performance of
SA-CT is comparable to temporal based methods on 3/4 benchmarks. To further
incorporate the temporal information, we propose a simple yet effective
Temporal Mixer module. The Temporal Mixer enhances the video representation and
improves the performance of the full SA-CT model, achieving very competitive
results. In this work, we also exploit large-scale pretrained models for
few-shot action recognition, providing useful insights for this research
direction
Horizontal Pyramid Matching for Person Re-identification
Despite the remarkable recent progress, person re-identification (Re-ID)
approaches are still suffering from the failure cases where the discriminative
body parts are missing. To mitigate such cases, we propose a simple yet
effective Horizontal Pyramid Matching (HPM) approach to fully exploit various
partial information of a given person, so that correct person candidates can be
still identified even even some key parts are missing. Within the HPM, we make
the following contributions to produce a more robust feature representation for
the Re-ID task: 1) we learn to classify using partial feature representations
at different horizontal pyramid scales, which successfully enhance the
discriminative capabilities of various person parts; 2) we exploit average and
max pooling strategies to account for person-specific discriminative
information in a global-local manner. To validate the effectiveness of the
proposed HPM, extensive experiments are conducted on three popular benchmarks,
including Market-1501, DukeMTMC-ReID and CUHK03. In particular, we achieve mAP
scores of 83.1%, 74.5% and 59.7% on these benchmarks, which are the new
state-of-the-arts. Our code is available on GithubComment: Accepted by AAAI 201
Suppression of <i>TREX1</i> deficiency-induced cellular senescence and interferonopathies by inhibition of DNA damage response
TREX1 encodes a major DNA exonuclease and mutations of this gene are associated with type I interferonopathies in human. Mice with Trex1 deletion or mutation have shortened life spans accompanied by a senescence-associated secretory phenotype. However, the contribution of cellular senescence in TREX1 deficiency-induced type I interferonopathies remains unknown. We found that features of cellular senescence present in Trex1−/− mice are induced by multiple factors, particularly DNA damage. The cGAS-STING and DNA damage response pathways are required for maintaining TREX1 deletion-induced cellular senescence. Inhibition of the DNA damage response, such as with Checkpoint kinase 2 (CHK2) inhibitor, partially alleviated progression of type I interferonopathies and lupus-like features in the mice. These data provide insights into the initiation and development of type I interferonopathies and lupus-like diseases, and may help inform the development of targeted therapeutics
Comparative Extracellular Proteomics of Aeromonas hydrophila Reveals Iron-Regulated Secreted Proteins as Potential Vaccine Candidates
In our previous study, several iron-related outer membrane proteins in Aeromonas hydrophila, a serious pathogen of farmed fish, conferred high immunoprotectivity to fish, and were proposed as potential vaccine candidates. However, the protective efficacy of these extracellular proteins against A. hydrophila remains largely unknown. Here, we identified secreted proteins that were differentially expressed in A. hydrophila LP-2 in response to iron starvation using an iTRAQ-based quantitative proteomics method. We identified 341 proteins, of which 9 were upregulated in response to iron starvation and 24 were downregulated. Many of the differently expressed proteins were associated with protease activity. We confirmed our proteomics results with Western blotting and qPCR. We constructed three mutants by knocking out three genes encoding differentially expressed proteins (Δorf01830, Δorf01609, and Δorf03641). The physiological characteristics of these mutants were investigated. In all these mutant strains, protease activity decreased, and Δorf01609, and Δorf01830 were less virulent in zebrafish. This indicated that the proteins encoded by these genes may play important roles in bacterial infection. We next evaluated the immune response provoked by the six iron-related recombinant proteins (ORF01609, ORF01830, ORF01839, ORF02943, ORF03355, and ORF03641) in zebrafish as well as the immunization efficacy of these proteins. Immunization with these proteins significantly increased the zebrafish immune response. In addition, the relative percent survival (RPS) of the immunized zebrafish was 50–80% when challenged with three virulent A. hydrophila strains, respectively. Thus, these extracellular secreted proteins might be effective vaccine candidates against A. hydrophila infection in fish
Precision Higgs physics at the CEPC
The discovery of the Higgs boson with its mass around 125 GeV by the ATLAS
and CMS Collaborations marked the beginning of a new era in high energy
physics. The Higgs boson will be the subject of extensive studies of the
ongoing LHC program. At the same time, lepton collider based Higgs factories
have been proposed as a possible next step beyond the LHC, with its main goal
to precisely measure the properties of the Higgs boson and probe potential new
physics associated with the Higgs boson. The Circular Electron Positron
Collider~(CEPC) is one of such proposed Higgs factories. The CEPC is an
circular collider proposed by and to be hosted in China. Located in a
tunnel of approximately 100~km in circumference, it will operate at a
center-of-mass energy of 240~GeV as the Higgs factory. In this paper, we
present the first estimates on the precision of the Higgs boson property
measurements achievable at the CEPC and discuss implications of these
measurements.Comment: 46 pages, 37 figure
中国の非研究型大学における女性教員のキャリアバリアに関する研究
内容の要約広島大学(Hiroshima University)博士(教育学)Doctor of Philosophy in Educationdoctora
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