5,798 research outputs found
Remove Cosine Window from Correlation Filter-based Visual Trackers: When and How
Correlation filters (CFs) have been continuously advancing the
state-of-the-art tracking performance and have been extensively studied in the
recent few years. Most of the existing CF trackers adopt a cosine window to
spatially reweight base image to alleviate boundary discontinuity. However,
cosine window emphasizes more on the central region of base image and has the
risk of contaminating negative training samples during model learning. On the
other hand, spatial regularization deployed in many recent CF trackers plays a
similar role as cosine window by enforcing spatial penalty on CF coefficients.
Therefore, we in this paper investigate the feasibility to remove cosine window
from CF trackers with spatial regularization. When simply removing cosine
window, CF with spatial regularization still suffers from small degree of
boundary discontinuity. To tackle this issue, binary and Gaussian shaped mask
functions are further introduced for eliminating boundary discontinuity while
reweighting the estimation error of each training sample, and can be
incorporated with multiple CF trackers with spatial regularization. In
comparison to the counterparts with cosine window, our methods are effective in
handling boundary discontinuity and sample contamination, thereby benefiting
tracking performance. Extensive experiments on three benchmarks show that our
methods perform favorably against the state-of-the-art trackers using either
handcrafted or deep CNN features. The code is publicly available at
https://github.com/lifeng9472/Removing_cosine_window_from_CF_trackers.Comment: 13 pages, 7 figures, submitted to IEEE Transactions on Image
Processin
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Advances and challenges in commercializing radiative cooling
Radiative cooling (RC) dissipates terrestrial heat to outer space through the atmospheric window, without external energy input and production of environmental pollutants. More and more efforts have been devoted to this clean promising cooling technology; thus diverse radiative coolers have emerged. However, the performance, cost, and effectiveness of various radiative coolers are not exactly the same. In addition, the large-scale application of RC technology is impeded by the low energy density, uncontrollable cooling power, and limited sky-facing area. Here, we critically review the recent progress of RC technology, evaluate the cooling performance of various radiative coolers, and discuss the challenges and feasible solutions to commercialize RC technology. Furthermore, valuable insights are provided to make new breakthroughs in this field
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Pulmonary diseases induced by ambient ultrafine and engineered nanoparticles in twenty-first century.
Air pollution is a severe threat to public health globally, affecting everyone in developed and developing countries alike. Among different air pollutants, particulate matter (PM), particularly combustion-produced fine PM (PM2.5) has been shown to play a major role in inducing various adverse health effects. Strong associations have been demonstrated by epidemiological and toxicological studies between increases in PM2.5 concentrations and premature mortality, cardiopulmonary diseases, asthma and allergic sensitization, and lung cancer. The mechanisms of PM-induced toxicological effects are related to their size, chemical composition, lung clearance and retention, cellular oxidative stress responses and pro-inflammatory effects locally and systemically. Particles in the ultrafine range (<100 nm), although they have the highest number counts, surface area and organic chemical content, are often overlooked due to insufficient monitoring and risk assessment. Yet, ample studies have demonstrated that ambient ultrafine particles have higher toxic potential compared with PM2.5. In addition, the rapid development of nanotechnology, bringing ever-increasing production of nanomaterials, has raised concerns about the potential human exposure and health impacts. All these add to the complexity of PM-induced health effects that largely remains to be determined, and mechanistic understanding on the toxicological effects of ambient ultrafine particles and nanomaterials will be the focus of studies in the near future
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Research on the performance of radiative cooling and solar heating coupling module to direct control indoor temperature
The energy crisis and environmental pollution pose great challenges to human development. Traditional vapor-compression cooling consumes abundant energy and leads to a series of environmental problems. Radiative cooling without energy consumption and environmental pollution holds great promise as the next generation cooling technology, applied in buildings mostly in indirect way. In this work, a temperature-regulating module was introduced for direct summer cooling and winter heating. Firstly, the summer experiments were conduct to investigate the radiative cooling performance of the module. And the results indicated that the maximum indoor temperature reached only 27.5 °C with the ambient temperature of 34 °C in low latitude areas and the air conditioning system was on for only about a quarter of the day. Subsequently, the winter experiments were performed to explore the performance of the module in cooling and heating modes. The results indicated that indoor temperature can reach 25 °C in the daytime without additional heat supply and about a quarter of the day didn't require heating in winter. Additionally, the transient model of the module and the building revealed that the electricity saving of 42.4% (963.5 kWh) can be achieved in cooling season with the module, and that was 63.7% (1449.1 kWh) when coupling with energy storage system. Lastly, further discussion about the challenges and feasible solutions for radiative cooling to directly combine with the buildings were provided to advance the application of radiative cooling. Furthermore, with an acceptable payback period of 8 years, the maximum acceptable incremental cost reached 26.2 $/m2. The work opens up a new avenue for the application mode of the daytime radiative cooling technology
Excited-state quantum phase transitions in the interacting boson model: Spectral characteristics of 0+ states and effective order parameter
The spectral characteristics of the Lπ=0+ excited states in the interacting boson model are systematically investigated. It is found that various types of excited-state quantum phase transitions may widely occur in the model as functions of the excitation energy, which indicates that the phase diagram of the interacting boson model can be dynamically extended along the direction of the excitation energy. It has also been justified that the d-boson occupation probability ρ(E) is qualified to be taken as the effective order parameter to identify these excited-state quantum phase transitions. In addition, the underlying relation between the excite-state quantum phase transition and the chaotic dynamics is also stated
A Generalized Iterated Shrinkage Algorithm for Non-convex Sparse Coding
2013 14th IEEE International Conference on Computer Vision, ICCV 2013, Sydney, NSW, 1-8 December 2013In many sparse coding based image restoration and image classification problems, using non-convex ℓp-norm minimization (0 ≤p <1) can often obtain better results than the convex ℓ1-norm minimization. A number of algorithms, e.g., iteratively reweighted least squares (IRLS), iteratively thresholding method (ITM-ℓp), and look-up table (LUT), have been proposed for non-convex ℓp-norm sparse coding, while some analytic solutions have been suggested for some specific values of p. In this paper, by extending the popular soft-thresholding operator, we propose a generalized iterated shrinkage algorithm (GISA) for ℓp-norm non-convex sparse coding. Unlike the analytic solutions, the proposed GISA algorithm is easy to implement, and can be adopted for solving non-convex sparse coding problems with arbitrary p values. Compared with LUT, GISA is more general and does not need to compute and store the look-up tables. Compared with IRLS and ITM-ℓp, GISA is theoretically more solid and can achieve more accurate solutions. Experiments on image restoration and sparse coding based face recognition are conducted to validate the performance of GISA.Department of ComputingRefereed conference pape
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