Open-World Weakly-Supervised Object Localization

While remarkable success has been achieved in weakly-supervised object localization (WSOL), current frameworks are not capable of locating objects of novel categories in open-world settings. To address this issue, we are the first to introduce a new weakly-supervised object localization task called OWSOL (Open-World Weakly-Supervised Object Localization). During training, all labeled data comes from known categories and, both known and novel categories exist in the unlabeled data. To handle such data, we propose a novel paradigm of contrastive representation co-learning using both labeled and unlabeled data to generate a complete G-CAM (Generalized Class Activation Map) for object localization, without the requirement of bounding box annotation. As no class label is available for the unlabelled data, we conduct clustering over the full training set and design a novel multiple semantic centroids-driven contrastive loss for representation learning. We re-organize two widely used datasets, i.e., ImageNet-1K and iNatLoc500, and propose OpenImages150 to serve as evaluation benchmarks for OWSOL. Extensive experiments demonstrate that the proposed method can surpass all baselines by a large margin. We believe that this work can shift the close-set localization towards the open-world setting and serve as a foundation for subsequent works. Code will be released at https://github.com/ryylcc/OWSOL

Recognize Anything: A Strong Image Tagging Model

We present the Recognize Anything Model (RAM): a strong foundation model for image tagging. RAM can recognize any common category with high accuracy. RAM introduces a new paradigm for image tagging, leveraging large-scale image-text pairs for training instead of manual annotations. The development of RAM comprises four key steps. Firstly, annotation-free image tags are obtained at scale through automatic text semantic parsing. Subsequently, a preliminary model is trained for automatic annotation by unifying the caption and tagging tasks, supervised by the original texts and parsed tags, respectively. Thirdly, a data engine is employed to generate additional annotations and clean incorrect ones. Lastly, the model is retrained with the processed data and fine-tuned using a smaller but higher-quality dataset. We evaluate the tagging capabilities of RAM on numerous benchmarks and observe impressive zero-shot performance, significantly outperforming CLIP and BLIP. Remarkably, RAM even surpasses the fully supervised manners and exhibits competitive performance with the Google API. We are releasing the RAM at \url{https://recognize-anything.github.io/} to foster the advancements of large models in computer vision

Hydrogen peroxide and glucose concentration measurement using optical fiber grating sensors with corrodible plasmonic nanocoatings

We propose and demonstrate hydrogen peroxide (H2O2) and glucose concentration measurements using a plasmonic optical fiber sensor. The sensor utilizes a tilted fiber Bragg grating (TFBG) written in standard single mode communication fiber. The fiber is over coated with an nm-scale film of silver that supports surface plasmon resonances (SPRs). Such a tilted grating SPR structure provides a high density of narrow spectral resonances (Q-factor about 105) that overlap with the broader absorption band of the surface plasmon waves in the silver film, thereby providing an accurate tool to measure small shifts of the plasmon resonance frequencies. The H2O2 to be detected acts as an oxidant to etch the silver film, which has the effect of gradually decreasing the SPR attenuation. The etching rate of the silver film shows a clear relationship with the H2O2 concentration so that monitoring the progressively increasing attenuation of a selected surface plasmon resonance over a few minutes enables us to measure the H2O2 concentration with a limit of detection of 0.2 µM. Furthermore, the proposed method can be applied to the determination of glucose in human serum for a concentration range from 0 to 12 mM (within the physiological range of 3-8 mM) by monitoring the H2O2 produced by an enzymatic oxidation process. The sensor does not require accurate temperature control because of the inherent temperature insensitivity of TFBG devices referenced to the core mode resonance. A gold mirror coated on the fiber allows the sensor to work in reflection, which will facilitate the integration of the sensor with a hypodermic needle for in vitro measurements. The present study shows that Ag-coated TFBG-SPR can be applied as a promising type of sensing probe for optical detection of H2O2 and glucose detection in human serum

Water-Assisted Diffusional Phase Transitions in Inorganic Metal Halide Perovskites

In experiments, water is observed to accelerate the black-yellow phase transition in inorganic metal halide perovskites (MHPs). However, the underlying microscopic mechanisms for this phenomenon remain unclear. In this study, we employ classical molecular dynamics simulations to examine the role of water molecules in the yellow-black phase transition in the typical inorganic MHP CsPbI3. Our simulation results demonstrate that the black-yellow phase transitions in CsPbI3 follow a crystal-amorphous-crystal two-step mechanism and that water molecules in the air can enter the amorphous interface between the black and yellow regions. The rate of the yellow-black phase transition markedly increases with the influx of interfacial water molecules, which enhance ion diffusivity by reducing the diffusion barrier, thereby expediting the yellow-black phase transition in CsPbI3. We discuss implications for the reverse black-yellow phase transition, which is known to degrade the photovoltaic properties of perovskites, and we present a general mechanism through which solvent molecules can greatly facilitate phase transitions that otherwise have prohibitively high transition energies

Discrepant expression of cytokines in inflammation- and age-related cataract patients.

PURPOSE: Inflammatory cataracts secondary to Behcet's disease (BD) or Vogt-Koyanagi-Harada disease (VKH) are thought to result from a pathological dysregulation of cytokines that is different from that of age-related (AR) cataracts. However, little is known about the function of cytokines in the development of inflammatory cataracts. The purpose of this study was to identify possible differences in cytokine expression in inflammation- and age-related cataract patients. METHODS: Analysis techniques involving the concomitant use of a cocktail of antibody-coated non-magnetic beads were used to determine the cytokine expression profiles of BD, VKH and AR cataract patients. Furthermore, anterior chamber aqueous flares and inflammatory cells were quantitatively measured with a laser flare cell meter (LFCM). RESULTS: The expressions of interleukin-2 (IL-2), IL-4, IL-6, IL-10, IL-17A, and interferon-γ (IFN-γ) were analyzed in aqueous humor (AqH), phytohemagglutinin (PHA)-stimulated and non-PHA-stimulated cultures of peripheral blood mononuclear cells (PBMCs) from the three types of cataract patients. IL-6 and IFN-γ were identified above the detection limits, but, among the BD and VKH cataract patients, only the levels of IL-6 were significantly higher in both the AqH and PBMC non-PHA cultures compared with the levels observed in the AR cataract patients. In contrast, IFN-γ was significantly elevated in the AqH of the BD cataract patients compared with the VKH and AR cataract patients. In the PHA-stimulated PBMC cultures, IL-2, IFN-γ, IL-6, and IL-17A were significantly increased, and the IL-6 level was significantly higher in the VKH patients than in the BD and AR cataract patients. The correlation analyses of the cytokines and inflammation indexes of the AqH obtained with the LFCM revealed that only IL-6 was significantly correlated with the inflammation index. CONCLUSION: Distinct expression profiles of cytokines and the correlations of these profiles with in vivo inflammatory indexes for inflammatory and AR cataract patients were identified

In-Fiber Closed Cavity Interferometric High-Resolution Aqueous Solution and Alcohol Gas Refractometer

An optical fiber interferometric refractometer for alcohol gas concentration and low refractive index (RI) solution (with 1.33−1.38 RI range) measurement is theoretically and experimentally demonstrated. The refractometer is based on a single-mode thin-core single-mode (STS) interferometric structure. By embedding a suitably sized air cavity at the splicing point, high-order cladding modes are successfully excited, which makes the sensor more suitable for low RI solution measurement. The effect of the air cavity’s diameter on the sensitivity of alcohol gas concentration was analyzed experimentally, which proved that RI sensitivity will increase with an enlarged diameter of the air cavity. On this basis, the air cavity is filled with graphene in order to improve the sensitivity of the sensor; and the measured sensitivity of the alcohol gas concentration is −1206.1 pm/%. Finally, the characteristics of the single-cavity structure, graphene-filled structure and double-cavity structure sensors are demonstrated, and the linear RI sensitivities are −54.593 nm/RIU (refractive index unit), −85.561 nm/RIU and 359.77 nm/RIU, respectively. Moreover, these sensor structures have the advantages of being compact and easily prepared

Biological sample measurement using a 10° tilted fiber grating sensing probe

High sensitivity biological sample measurement has been achieved by using a 10° tilted fiber Bragg grating. Human acute leukemia cells with different intracellular densities were clearly discriminated by identifying their slight refraction index (RI) perturbations in the range from 1.3342 to 1.3344, combining with a temperature self-calibration property

Orientation-recognized rotation measurement using single polarimetric multi-mode tilted fiber grating

The polarimetric sensing characteristics of multi-mode-fiber based tilted fiber Bragg grating (MMF-TFBG) have been analyzed and expe

Comparisons of the mean cytokine levels in the aqueous humor samples among the three groups via ANOVA.

<p><b>Footnotes:</b> *P <0.05 versus the AR samples.</p><p>Comparisons of the mean cytokine levels in the aqueous humor samples among the three groups via ANOVA.</p