63 research outputs found
CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Models
Camouflaged Object Detection (COD) is a challenging task in computer vision
due to the high similarity between camouflaged objects and their surroundings.
Existing COD methods primarily employ semantic segmentation, which suffers from
overconfident incorrect predictions. In this paper, we propose a new paradigm
that treats COD as a conditional mask-generation task leveraging diffusion
models. Our method, dubbed CamoDiffusion, employs the denoising process of
diffusion models to iteratively reduce the noise of the mask. Due to the
stochastic sampling process of diffusion, our model is capable of sampling
multiple possible predictions from the mask distribution, avoiding the problem
of overconfident point estimation. Moreover, we develop specialized learning
strategies that include an innovative ensemble approach for generating robust
predictions and tailored forward diffusion methods for efficient training,
specifically for the COD task. Extensive experiments on three COD datasets
attest the superior performance of our model compared to existing
state-of-the-art methods, particularly on the most challenging COD10K dataset,
where our approach achieves 0.019 in terms of MAE
DiffusionFace: Towards a Comprehensive Dataset for Diffusion-Based Face Forgery Analysis
The rapid progress in deep learning has given rise to hyper-realistic facial
forgery methods, leading to concerns related to misinformation and security
risks. Existing face forgery datasets have limitations in generating
high-quality facial images and addressing the challenges posed by evolving
generative techniques. To combat this, we present DiffusionFace, the first
diffusion-based face forgery dataset, covering various forgery categories,
including unconditional and Text Guide facial image generation, Img2Img,
Inpaint, and Diffusion-based facial exchange algorithms. Our DiffusionFace
dataset stands out with its extensive collection of 11 diffusion models and the
high-quality of the generated images, providing essential metadata and a
real-world internet-sourced forgery facial image dataset for evaluation.
Additionally, we provide an in-depth analysis of the data and introduce
practical evaluation protocols to rigorously assess discriminative models'
effectiveness in detecting counterfeit facial images, aiming to enhance
security in facial image authentication processes. The dataset is available for
download at \url{https://github.com/Rapisurazurite/DiffFace}
A fourth-order Runge-Kutta in the interaction picture method for coupled nonlinear Schrodinger equation
A fourth-order Runge-Kutta in the interaction picture (RK4IP) method is
presented for solving the coupled nonlinear Schrodinger equation (CNLSE) that
governs the light propagation in optical fibers with randomly varying
birefringence. The computational error of RK4IP is caused by the fourth-order
Runge-Kutta algorithm, better than the split-step approximation limited by the
step size. As a result, the step size of RK4IP can have the same order of
magnitude as the dispersion length and/or the nonlinear length of the fiber,
provided the birefringence effect is small. For communication fibers with
random birefringence, the step size of RK4IP can be orders of magnitude larger
than the correlation length and the beating length of the fibers, depending on
the interaction between linear and nonlinear effects. Our approach can be
applied to the fibers having the general form of local birefringence and treat
the Kerr nonlinearity without approximation. For the systems with realistic
parameters, the RK4IP results are consistent with those using Manakov-PMD
approximation. However, increased interaction between the linear and nonlinear
terms in CNLSE leads to increased discrepancy between RK4IP and Manakov-PMD
approximation.Comment: 12 pages, 4 figures, 1 Table, submitted to Optics Express
Preliminary Design of a Small Unmanned Battery Powered Tailsitter
This paper presents a preliminary design methodology for small unmanned battery powered tailsitters. Subsystem models, including takeoff weight, power and energy consumption models, and battery discharge model, were investigated, respectively. Feasible design space was given by simulation with mission and weight constraints, while the influences of wing loading and battery ratio were analyzed. Case study was carried out according to the design process, and the results were validated by previous designs. The design methodology can be used to determine key parameters and make necessary preparations for detailed design and vehicle realization of small battery powered tailsitters
Long-term Survival of Personalized Surgical Treatment of Locally Advanced Non-small Cell Lung Cancer Based on Molecular Staging
Background and objective Approximately 35%-40% of patients with newly diagnosed non-small cell Lung cancer have locally advanced disease. The average survival time of these patients only have 6-8 months with chemotherapy. The aim of this study is to explore and summarize the probability of detection of micrometastasis in peripheral blood for molecular staging, and for selection of indication of surgical treatment, and beneficiary of neoadjuvant chemotherapy and postoperative adjuvant therapy in locally advanced lung cancer; to summarize the long-time survival result of personalized surgical treatment of 516 patients with locally advanced non-small cell lung cancer based on molecular staging methods. Methods CK19 mRNA expression of peripheral blood samples was detected in 516 lung cancer patients by RT-PCR before operation for molecular diagnosis of micrometastasis, personalized molecular staging, and for selection of indication of surgical treatment and the beneficiary of neoadjuvant chemotherapy and postoperative adjuvant therapy in patients with locally advanced nonsmall cell lung cancer invaded heart, great vessels or both. The long-term survival result of personalized surgical treatment was retrospectively analyzed in 516 patients with locally advanced non-small cell lung cancer based on molecular staging methods. Results There were 322 patients with squamous cell carcinoma and 194 cases with adenocarcinoma in the series of 516 patients with locally advanced lung cancer involved heart, great vessels or both. There were 112 patients with IIIA disease and 404 cases with IIIB disease according to P-TNM staging. There were 97 patients with M-IIIA disease, 278 cases with M-IIIB disease and 141 cases with III disease according to our personalized molecular staging. Of the 516 patients, bronchoplastic procedures and pulmonary artery reconstruction was carried out in 256 cases; lobectomy combined with resection and reconstruction of partial left atrium was performed in 41 cases; Double sleeve lobectomy combined with resection and reconstruction of super vena cava was carried out in 90 cases; Lobectomy combined with resection and reconstruction of diaphragm was performed in 3 cases; Double sleeve lobectomy combined with resection and reconstruction of partial left atrium was performed in 30 cases; Bronchoplastic procedures and pulmonary artery reconstruction combined with reconstruction of aorta sheath was carried out in 10 cases; Right pneumonectomy combined with resection and reconstruction partial left atrium, total right diaphragm with Dacron, and post cava and right liver vein was performed in one case; Lobectomy combined with resection and reconstruction of carina was carried out in 10 cases; Bronchoplastic procedures and pulmonary artery reconstruction combined with resection and reconstruction of carina and superior vane cava, or combined with superior vena cava and left atrium, or with carina and left atrium was performed in 55 cases in this series. Five patients died of operative complications and the operative mortality was 0.97%. CK19 mRNA expression was found in 141 patients. The positive rate of CK19 mRNA expression was 27.3% in peripheral blood samples in the 516 cases. The positive rates of micrometastasis in peripheral blood was significantly related to histological classification, P-TNM staging and N staging of the cancer (P < 0.05), but not to age, sex, smoking status of the patients, and size of primary tumor, and locations of the tumor (P > 0.05). The median survival time was 43.74 months. The 1, 3, 5 and 10 year survival rates of the 516 cases was 89.1%, 39.3%, 19.8% and 10.4%, respectively. The postoperative survival rate was remarkably correlated with micrometastasis in peripheral blood, histological classification of the tumor, size of primary cancer and lymph mode involvement (P < 0.05). The results of multivariable Cox model analysis showed that "personalizedmolecular P-TNM staging", micrometastasis in peripheral blood, pathological types of the tumor and mediastinal lymph node metastasis of the cancer were the most significant factors for predicting prognosis in the patients with locally advanced nonsmall lung cancer. Conclusion (1) Micrometastasis was existed in peripheral blood of patients with lung cancer, which can not be detected with conventional methods. (2) Detecting of CK19 mRNA expression in peripheral blood in lung cancer patients can be used for diagnosis of micrometastasis of lung cancer and “molecular staging” and “molecular P-TNM staging” for lung cancer patients. It will be helpful for selection of surgical treatment indication, the beneficiary of neoadjuvant chemotherapy and postopertive adjuvant therapy in the patients with locally advanced non-small cell lung cancer. (3) Personalized surgical treatment can significantly improve prognosis and increase curative rate and long-term survival rate of locally advanced nonsmall cell lung cancer based on personalized molecular staging
Land use change and climate variation in the Three Gorges Reservoir Catchment from 2000 to 2015 based on the Google Earth Engine
Possible environmental change and ecosystem degradation have received increasing attention since the construction of Three Gorges Reservoir Catchment (TGRC) in China. The advanced Google Earth Engine (GEE) cloud-based platform and the large number of Geosciences and Remote Sensing datasets archived in GEE were used to analyze the land use and land cover change (LULCC) and climate variation in TGRC. GlobeLand30 data were used to evaluate the spatial land dynamics from 2000 to 2010 and Landsat 8 Operational Land Imager (OLI) images were applied for land use in 2015. The interannual variations in the Land Surface Temperature (LST) and seasonally integrated normalized difference vegetation index (SINDVI) were estimated using Moderate Resolution Imaging Spectroradiometer (MODIS) products. The climate factors including air temperature, precipitation and evapotranspiration were investigated based on the data from the Global Land Data Assimilation System (GLDAS). The results indicated that from 2000 to 2015, the cultivated land and grassland decreased by 2.05% and 6.02%, while the forest, wetland, artificial surface, shrub land and waterbody increased by 3.64%, 0.94%, 0.87%, 1.17% and 1.45%, respectively. The SINDVI increased by 3.209 in the period of 2000-2015, while the LST decreased by 0.253 °C from 2001 to 2015. The LST showed an increasing trend primarily in urbanized area, with a decreasing trend mainly in forest area. In particular, Chongqing City had the highest LST during the research period. A marked decrease in SINDVI occurred primarily in urbanized areas. Good vegetation areas were primarily located in the eastern part of the TGRC, such as Wuxi County, Wushan County, and Xingshan County. During the 2000–2015 period, the air temperature, precipitation and evapotranspiration rose by 0.0678 °C/a, 1.0844 mm/a, and 0.4105 mm/a, respectively. The climate change in the TGRC was influenced by LULCC, but the effect was limited. What is more, the climate change was affected by regional climate change in Southwest China. Marked changes in land use have occurred in the TGRC, and they have resulted in changes in the LST and SINDVI. There was a significantly negative relationship between LST and SINDVI in most parts of the TGRC, especially in expanding urban areas and growing forest areas. Our study highlighted the importance of environmental protection, particularly proper management of land use, for sustainable development in the catchment
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