TIDE: Test Time Few Shot Object Detection

Few-shot object detection (FSOD) aims to extract semantic knowledge from limited object instances of novel categories within a target domain. Recent advances in FSOD focus on fine-tuning the base model based on a few objects via meta-learning or data augmentation. Despite their success, the majority of them are grounded with parametric readjustment to generalize on novel objects, which face considerable challenges in Industry 5.0, such as (i) a certain amount of fine-tuning time is required, and (ii) the parameters of the constructed model being unavailable due to the privilege protection, making the fine-tuning fail. Such constraints naturally limit its application in scenarios with real-time configuration requirements or within black-box settings. To tackle the challenges mentioned above, we formalize a novel FSOD task, referred to as Test TIme Few Shot DEtection (TIDE), where the model is un-tuned in the configuration procedure. To that end, we introduce an asymmetric architecture for learning a support-instance-guided dynamic category classifier. Further, a cross-attention module and a multi-scale resizer are provided to enhance the model performance. Experimental results on multiple few-shot object detection platforms reveal that the proposed TIDE significantly outperforms existing contemporary methods. The implementation codes are available at https://github.com/deku-0621/TID

Boosting Few-shot Action Recognition with Graph-guided Hybrid Matching

Class prototype construction and matching are core aspects of few-shot action recognition. Previous methods mainly focus on designing spatiotemporal relation modeling modules or complex temporal alignment algorithms. Despite the promising results, they ignored the value of class prototype construction and matching, leading to unsatisfactory performance in recognizing similar categories in every task. In this paper, we propose GgHM, a new framework with Graph-guided Hybrid Matching. Concretely, we learn task-oriented features by the guidance of a graph neural network during class prototype construction, optimizing the intra- and inter-class feature correlation explicitly. Next, we design a hybrid matching strategy, combining frame-level and tuple-level matching to classify videos with multivariate styles. We additionally propose a learnable dense temporal modeling module to enhance the video feature temporal representation to build a more solid foundation for the matching process. GgHM shows consistent improvements over other challenging baselines on several few-shot datasets, demonstrating the effectiveness of our method. The code will be publicly available at https://github.com/jiazheng-xing/GgHM.Comment: Accepted by ICCV202

Imposing implicit feasibility constraints on deformable image registration using a statistical generative model

Purpose: Deformable registration problems are conventionally posed in a regularized optimization framework, where balance between fidelity and prescribed regularization usually needs to be tuned for each case. Even so, using a single weight to control regularization strength may be insufficient to reflect spatially variant tissue properties and limit registration performance. In this study, we proposed to incorporate a spatially variant deformation prior into image registration framework using a statistical generative model. Approach: A generator network is trained in an unsupervised setting to maximize the likelihood of observing the moving and fixed image pairs, using an alternating back-propagation approach. The trained model imposes constraints on deformation and serves as an effective low-dimensional deformation parametrization. During registration, optimization is performed over this learned parametrization, eliminating the need for explicit regularization and tuning. The proposed method was tested against SimpleElastix, DIRNet, and Voxelmorph. Results: Experiments with synthetic images and simulated CTs showed that our method yielded registration errors significantly lower than SimpleElastix and DIRNet. Experiments with cardiac magnetic resonance images showed that the method encouraged physical and physiological feasibility of deformation. Evaluation with left ventricle contours showed that our method achieved a dice of ( 0.93±0.03 ) with significant improvement over all SimpleElastix options, DIRNet, and VoxelMorph. Mean average surface distance was on millimeter level, comparable to the best SimpleElastix setting. The average 3D registration time was 12.78 s, faster than 24.70 s in SimpleElastix. Conclusions: The learned implicit parametrization could be an efficacious alternative to regularized B-spline model, more flexible in admitting spatial heterogeneity

MRA-free intracranial vessel localization on MR vessel wall images.

Analysis of vessel morphology is important in assessing intracranial atherosclerosis disease (ICAD). Recently, magnetic resonance (MR) vessel wall imaging (VWI) has been introduced to image ICAD and characterize morphology for atherosclerotic lesions. In order to automatically perform quantitative analysis on VWI data, MR angiography (MRA) acquired in the same imaging session is typically used to localize the vessel segments of interest. However, MRA may be unavailable caused by the lack or failure of the sequence in a VWI protocol. This study aims to investigate the feasibility to infer the vessel location directly from VWI. We propose to synergize an atlas-based method to preserve general vessel structure topology with a deep learning network in the motion field domain to correct the residual geometric error. Performance is quantified by examining the agreement between the extracted vessel structures from the pair-acquired and alignment-corrected angiogram, and the estimated output using a cross-validation scheme. Our proposed pipeline yields clinically feasible performance in localizing intracranial vessels, demonstrating the promise of performing vessel morphology analysis using VWI alone

In Situ Surface-Enhanced Infrared Absorption Spectroscopy of Aqueous Molecules with Facile-Prepared Large-Area Reduced Graphene Oxide Island Film

Midinfrared plasmons in patterned graphene could advance the development of surface-enhanced infrared absorption spectroscopy (SEIRAS). However, limitation in measuring the extinction spectra with transmission and external reflection configurations greatly restricts the analyses of aqueous samples. In addition, complicated, time- and cost-consuming preparation of patterned graphene also limits its progress. Here we demonstrate a facile-prepared large-scale reduced graphene oxide island film on a total internal reflection silicon prism, which not only shows a prominent enhancement effect in mid-infrared region but also effectively eliminates the contribution of bulk solution by optical near-field effect. As a result, the entire vibrational fingerprints of methylene blue monolayer in aqueous solution can be acquired with high sensitivity in real time. Our work extends the application of graphene-based SEIRAS to aqueous environment, breaking through previously unattainable technology

Hidropsia endolinfática experimental sob ação de inibidor da óxido nítrico sintase tipo II: avaliação com emissões otoacústicas e eletrococleografia Experimental endolymphatic hydrops under action of a type II nitric oxide synthase inhibitor: otoacoustic emissions evaluation and electrocochleography

No modelo experimental de hidropsia endolinfática há redução na amplitude das emissões otoacústicas produtos de distorção (EOAPD) e elevação nos limiares eletrofisiológicos na eletrococleografia. Estudos mostraram que há expressão da óxido nítrico sintase tipo II (ONS II) na cóclea com hidropsia, sugerindo a participação do óxido nítrico (ON) na patogênese desta doença. O objetivo deste trabalho foi avaliar a ação de um inibidor da ONS II nas EOAPD e eletrococleografia em cobaias com hidropisia endolinfática experimental. MATERIAL E MÉTODOS: Foram estudadas 16 cobaias nas quais se induziu hidropsia endolinfática experimental por obliteração do ducto e saco endolinfático na orelha direita durante 16 semanas, divididas em dois grupos: oito cobaias recebendo um inibidor da ONS II, a aminoguanidina, por via oral e um grupo de oito cobaias como controle. Comparamos as amplitudes das EOAPD nas médias geométricas de freqüências de 1062, 2187, 4375 e 7000Hz, os limiares eletrofisiológicos nas freqüências de 1000, 2000, 4000 e 6000Hz e a relação entre os potenciais de somação e de ação (PS/PA) entre os grupos. RESULTADOS: Não houve diferença significante nas EOAPD e na relação PS/PA entre os grupos. O grupo que recebeu a aminoguanidina apresentou menor elevação nos limiares eletrofisiológicos nas freqüências de 2000 (p<0,05) e 6000 Hz (p<0,05) na 12ª semana e nas freqüências de 1000 (p<0,05), 2000 (p<0,001), 4000 (p<0,001) e 6000Hz (p<0,001) na 16ª semana. CONCLUSÕES: O inibidor da ONS II reduziu a elevação dos limiares eletrofisiológicos na eletrococleografia na hidropsia endolinfática experimental.<br>In experimental endolymphatic hydrops distortion-products otoacoustic emission (dpoae) amplitudes decrease and there is elevation on electrocochleographic thresholds. Some authors found type ii nitric oxide synthase (nos ii) expression in hydropic cochleas and they suggest nitric oxide (no) may be involved in endolymphatic hydrops pathogenesis. The aim of this study was to evaluate the action of a nos ii inhibitor on dpoae and electrocochleography in experimental endolymphatic hydrops. MATERIAL E METHODS: endolymphatic hydrops was induced in 16 guinea pigs by obliterating the endolymphatic duct and sac in the right ear. They were divided in two groups: eigth guinea pigs under the action of aminoguanidine, a nos ii inhibitor and eigth control guinea pigs. We compared dpoae amplitudes at geometric means of frequencies 1062, 2187, 4375 and 7000 hz, compound action potential threshold at 1000, 2000, 4000 and 6000 hz and summating potential to action potential (sp/ap) ratio between the groups during the postoperative observation period of 16 weeks. RESULTS: there were no significant changes in the dpoae amplitudes and in the sp/ap ratio. The group that received aminoguanidine had a lower degree of threshold increase at 2000 (p<0.05) And 6000 hz (p<0.05) In 12th postoperative week and at 1000 (p<0.05), 2000 (P<0.001), 4000 (P<0.001) And 6000 hz (p<0.001) At 16th postoperative week. CONCLUSIONS: nos ii inhibitor decreased the electrocochleography threshold elevation on experimental endolymphatic hydrops