99 research outputs found

    Image Quality Is Not All You Want: Task-Driven Lens Design for Image Classification

    Full text link
    In computer vision, it has long been taken for granted that high-quality images obtained through well-designed camera lenses would lead to superior results. However, we find that this common perception is not a "one-size-fits-all" solution for diverse computer vision tasks. We demonstrate that task-driven and deep-learned simple optics can actually deliver better visual task performance. The Task-Driven lens design approach, which relies solely on a well-trained network model for supervision, is proven to be capable of designing lenses from scratch. Experimental results demonstrate the designed image classification lens (``TaskLens'') exhibits higher accuracy compared to conventional imaging-driven lenses, even with fewer lens elements. Furthermore, we show that our TaskLens is compatible with various network models while maintaining enhanced classification accuracy. We propose that TaskLens holds significant potential, particularly when physical dimensions and cost are severely constrained.Comment: Use an image classification network to supervise the lens design from scratch. The final designs can achieve higher accuracy with fewer optical element

    Learnable Reconstruction Methods from RGB Images to Hyperspectral Imaging: A Survey

    Full text link
    Hyperspectral imaging enables versatile applications due to its competence in capturing abundant spatial and spectral information, which are crucial for identifying substances. However, the devices for acquiring hyperspectral images are expensive and complicated. Therefore, many alternative spectral imaging methods have been proposed by directly reconstructing the hyperspectral information from lower-cost, more available RGB images. We present a thorough investigation of these state-of-the-art spectral reconstruction methods from the widespread RGB images. A systematic study and comparison of more than 25 methods has revealed that most of the data-driven deep learning methods are superior to prior-based methods in terms of reconstruction accuracy and quality despite lower speeds. This comprehensive review can serve as a fruitful reference source for peer researchers, thus further inspiring future development directions in related domains

    Triplet Attention Transformer for Spatiotemporal Predictive Learning

    Full text link
    Spatiotemporal predictive learning offers a self-supervised learning paradigm that enables models to learn both spatial and temporal patterns by predicting future sequences based on historical sequences. Mainstream methods are dominated by recurrent units, yet they are limited by their lack of parallelization and often underperform in real-world scenarios. To improve prediction quality while maintaining computational efficiency, we propose an innovative triplet attention transformer designed to capture both inter-frame dynamics and intra-frame static features. Specifically, the model incorporates the Triplet Attention Module (TAM), which replaces traditional recurrent units by exploring self-attention mechanisms in temporal, spatial, and channel dimensions. In this configuration: (i) temporal tokens contain abstract representations of inter-frame, facilitating the capture of inherent temporal dependencies; (ii) spatial and channel attention combine to refine the intra-frame representation by performing fine-grained interactions across spatial and channel dimensions. Alternating temporal, spatial, and channel-level attention allows our approach to learn more complex short- and long-range spatiotemporal dependencies. Extensive experiments demonstrate performance surpassing existing recurrent-based and recurrent-free methods, achieving state-of-the-art under multi-scenario examination including moving object trajectory prediction, traffic flow prediction, driving scene prediction, and human motion capture.Comment: Accepted to WACV 202

    A Family of Lanthanide Noncentrosymmetric Superconductors La4_4TXTX (TT = Ru, Rh, Ir; XX = Al, In)

    Full text link
    We report the discovery of superconductivity in a series of noncentrosymmetric compounds La4_4TXTX (TT = Ru, Rh, Ir; XX = Al, In), which have a cubic crystal structure with space group F4ˉ3mF\bar{4}3m. La4_4RuAl, La4_4RhAl, La4_4IrAl, La4_4RuIn and La4_4IrIn exhibit bulk superconducting transitions with critical temperatures TcT_c of 1.77 K, 3.05 K, 1.54 K, 0.58 K and 0.93 K, respectively. The specific heat of the La4_4TTAl compounds are consistent with an ss-wave model with a fully open superconducting gap. In all cases, the upper critical fields are well described by the Werthamer-Helfand-Hohenberg model, and the values are well below the Pauli limit, indicating that orbital limiting is the dominant pair-breaking mechanism. Density functional theory (DFT) calculations reveal that the degree of band splitting by the antisymmetric spin-orbit coupling (ASOC) shows considerable variation between the different compounds. This indicates that the strength of the ASOC is highly tunable across this series of superconductors, suggesting that these are good candidates for examining the relationship between the ASOC and superconducting properties in noncentrosymmetric superconductors.Comment: 10 pages, 7 figure

    Sensitive and Ultrabroadband Phototransistor Based on Two-Dimensional Bi2O2Se Nanosheets

    Get PDF
    Bi2O2Se, a high-mobility and air-stable 2D material, has attracted substantial attention for application in integrated logic electronics and optoelectronics. However, achieving an overall high performance over a wide spectral range for Bi2O2Se-based devices remains a challenge. A broadband phototransistor with high photoresponsivity (R) is reported that comprises high-quality large-area (≈180 µm) Bi2O2Se nanosheets synthesized via a modified chemical vapor deposition method with a face-down configuration. The device covers the ultraviolet (UV), visible (Vis), and near-infrared (NIR) wavelength ranges (360–1800 nm) at room temperature, exhibiting a maximum R of 108 696 A W−1 at 360 nm. Upon illumination at 405 nm, the external quantum efficiency, R, and detectivity (D*) of the device reach up to 1.5 × 107%, 50055 A W−1, and 8.2 × 1012 Jones, respectively, which is attributable to a combination of the photogating, photovoltaic, and photothermal effects. The devices reach a −3 dB bandwidth of 5.4 kHz, accounting for a fast rise time (τrise) of 32 µs. The high sensitivity, fast response time, and environmental stability achieved simultaneously in these 2D Bi2O2Se phototransistors are promising for high-quality UV and IR imaging applications

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

    Get PDF
    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

    Radio Coverage Mapping in Wireless Sensor Networks

    No full text
    corecore