Noisy Label Processing for Classification: A Survey

In recent years, deep neural networks (DNNs) have gained remarkable achievement in computer vision tasks, and the success of DNNs often depends greatly on the richness of data. However, the acquisition process of data and high-quality ground truth requires a lot of manpower and money. In the long, tedious process of data annotation, annotators are prone to make mistakes, resulting in incorrect labels of images, i.e., noisy labels. The emergence of noisy labels is inevitable. Moreover, since research shows that DNNs can easily fit noisy labels, the existence of noisy labels will cause significant damage to the model training process. Therefore, it is crucial to combat noisy labels for computer vision tasks, especially for classification tasks. In this survey, we first comprehensively review the evolution of different deep learning approaches for noisy label combating in the image classification task. In addition, we also review different noise patterns that have been proposed to design robust algorithms. Furthermore, we explore the inner pattern of real-world label noise and propose an algorithm to generate a synthetic label noise pattern guided by real-world data. We test the algorithm on the well-known real-world dataset CIFAR-10N to form a new real-world data-guided synthetic benchmark and evaluate some typical noise-robust methods on the benchmark

Neural Categorical Priors for Physics-Based Character Control

Recent advances in learning reusable motion priors have demonstrated their effectiveness in generating naturalistic behaviors. In this paper, we propose a new learning framework in this paradigm for controlling physics-based characters with significantly improved motion quality and diversity over existing state-of-the-art methods. The proposed method uses reinforcement learning (RL) to initially track and imitate life-like movements from unstructured motion clips using the discrete information bottleneck, as adopted in the Vector Quantized Variational AutoEncoder (VQ-VAE). This structure compresses the most relevant information from the motion clips into a compact yet informative latent space, i.e., a discrete space over vector quantized codes. By sampling codes in the space from a trained categorical prior distribution, high-quality life-like behaviors can be generated, similar to the usage of VQ-VAE in computer vision. Although this prior distribution can be trained with the supervision of the encoder's output, it follows the original motion clip distribution in the dataset and could lead to imbalanced behaviors in our setting. To address the issue, we further propose a technique named prior shifting to adjust the prior distribution using curiosity-driven RL. The outcome distribution is demonstrated to offer sufficient behavioral diversity and significantly facilitates upper-level policy learning for downstream tasks. We conduct comprehensive experiments using humanoid characters on two challenging downstream tasks, sword-shield striking and two-player boxing game. Our results demonstrate that the proposed framework is capable of controlling the character to perform considerably high-quality movements in terms of behavioral strategies, diversity, and realism. Videos, codes, and data are available at https://tencent-roboticsx.github.io/NCP/

Changes in clinical and CT manifestations related to liver abscesses in patients with vs. without basic diabetes mellitus before and after CT-guided interventional therapy: An observational study

Purpose: To explore differences in the changes of clinical and CT manifestations related to liver abscess before and after CT-guided interventional therapy between patients with and without Diabetes Mellitus (DM). Materials and methods: Fifty-eight consecutive patients with liver abscesses were retrospectively enrolled in this study. All patients underwent upper abdominal contrast-enhanced CT scans before and after CT-guided interventional therapy. They were divided into two groups including the DM group (n=30) and the Non-DM group (n=28) if the liver abscess occurred in patients with and without DM, respectively. The changes in the clinical and CT manifestations related to liver abscess after CT-guided interventional therapy in both groups were statistically analyzed. Results: After CT-guided interventional therapy, the length of hospital stay, white blood cell recovery time and drainage tube removal time in the DM group were longer than in the Non-DM group (all p-values < 0.05). The incidence of postoperative complications in the DM group was higher than in the Non-DM group (p < 0.05). As shown on CT, the postoperative reduced percentage of maximum diameter of abscess cavity and the reduction rate of edema band surrounding the liver abscess in the DM group were smaller than in the Non-DM group (both p-values < 0.05). The time intervals of the previous characteristic changes on CT before and after interventional therapy in the DM group were longer than in the Non-DM group (all p-values < 0.05). Conclusions: The liver abscesses patients with DM could not have a faster recovery and better therapeutic effect than those without DM after the CT-guided interventional therapy

An Optimal Method For Product Selection By Using Online Ratings And Considering Search Costs

With the collecting and publishing data about consumers purchasing and browsing products at the platform of online, this data prodives new ways to better understand the consumers search behavior before purchase. How to base on consumers online search behavior and simutaneously consider offline experience costs is worth studying. An optimal method based on the utility of the attribute of product is proposed. The proposed method follows steps below. Firstly, based on the multi-attribute utility theory, the overall utility of product is calculated by using ratings data. Secondly, the overall utility is combined into the original sequential search model to find the optimal selection strategy. Thirdly, the candidate product sets arranged in descending order of the reservation utilities are finally obtained. Finally, taking the online ratings data provided by a comprehensive automobile website as an example, lastly the proposed method is simulated and compared with other method. The result shows that the proposed method is feasible and effective

Factors Associated with the Implementation of Integrated Medical-elderly-nursing Services：a Review Using the Consolidated Framework for Implementation Research

The problem of health and pension in an aging society is becoming increasingly acute. Under the promotion of Chinese policy of combining medical care with nursing care and the hierarchical diagnosis and treatment system. Hangzhou City, Zhejiang Province, has pioneered integrated medical-elderly-nursing services to meet the healthcare needs of an aging society. The initial effects of the services have been shown, but there are so many influencing factors associated with the delivery. And the relevant influencing factors are lack of systematic and comprehensive analysis. Therefore, summarizing the factors associated with the implementation of the services and described them in terms of five aspects (intervention characteristics, outer setting, inner setting, characteristics of individuals, process) with the help of Consolidated Framework for Implementation Research. The major facilitators to implementing IMSs were as follows: diversified and individualized services, close and long-term cooperation between the healthcare institution delivering IMSs and other institutions in the regional medical consortium, clear determination of the duties of each member in the service team, incentives from hospital or other institutions. The major barriers were: lack of flexibility and ignoring individual characteristics in delivering some services, for example, health management; inadequate levels of diagnosis and treatment; insufficient workers, equipment, and drugs

Seasonal temperature response over the Indochina Peninsula to a worst-case high-emission forcing: a study with the regionally coupled model ROM

Changes of surface air temperature (SAT) over the Indochina Peninsula (ICP) under the Representative Concentration Pathway (RCP) 8.5 scenario are projected for wet and dry seasons in the short-term (2020–2049) and long-term (2070–2099) future of the twenty-first century. A first analysis on projections of the SAT by the state-of-the-art regionally coupled atmosphere-ocean model ROM, including exchanges of momentum, heat, and water fluxes between the atmosphere (Regional Model) and ocean (Max Planck Institute Ocean Model) models, shows the following results: (i) In both seasons, the highest SAT occurs over the southern coastal area while the lowest over the northern mountains. The highest warming magnitudes are located in the northwestern part of the ICP. The regionally averaged SAT over the ICP increases by 2.61 °C in the wet season from short- to long-term future, which is slightly faster than that of 2.50 °C in the dry season. (ii) During the short-term future, largest SAT trends occur over the southeast and northwest ICP in wet and dry seasons, respectively. On regional average, the wet season is characterized by a significant warming rate of 0.22 °C decade−1, while it is non-significant with 0.11 °C decade−1for the dry season. For the long-term future, the rapid warming is strengthened significantly over whole ICP, with trends of 0.51 °C decade−1and 0.42 °C decade−1in wet and dry seasons,respectively. (iii) In the long-term future, more conspicuous warming is noted, especially in the wet season, due to the increased downward longwave radiation. Higher CO2concentrations enhancing the greenhouse effect can be attributed to the water vapor–greenhouse feedback, which, affecting atmospheric humidity and counter radiation, leads to the rising SAT

Magnesium-Rich Calcium Phosphate Derived from Tilapia Bone Has Superior Osteogenic Potential

We extracted magnesium-rich calcium phosphate bioceramics from tilapia bone using a gradient thermal treatment approach and investigated their chemical and physicochemical properties. X-ray diffraction showed that tilapia fish bone-derived hydroxyapatite (FHA) was generated through the first stage of thermal processing at 600–800 °C. Using FHA as a precursor, fish bone biphasic calcium phosphate (FBCP) was produced after the second stage of thermal processing at 900–1200 °C. The beta-tricalcium phosphate content in the FBCP increased with an increasing calcination temperature. The fact that the lattice spacing of the FHA and FBCP was smaller than that of commercial hydroxyapatite (CHA) suggests that Mg-substituted calcium phosphate was produced via the gradient thermal treatment. Both the FHA and FBCP contained considerable quantities of magnesium, with the FHA having a higher concentration. In addition, the FHA and FBCP, particularly the FBCP, degraded faster than the CHA. After one day of degradation, both the FHA and FBCP released Mg2+, with cumulative amounts of 4.38 mg/L and 0.58 mg/L, respectively. Furthermore, the FHA and FBCP demonstrated superior bone-like apatite formation; they are non-toxic and exhibit better osteoconductive activity than the CHA. In light of our findings, bioceramics originating from tilapia bone appear to be promising in biomedical applications such as fabricating tissue engineering scaffolds

2D Graphene oxide (GO) doped p-n type BiOI/Bi 2 WO 6 as a novel composite for photodegradation of bisphenol A (BPA) in aqueous solutions under UV-vis irradiation

Abstract(#br)Bisphenol A (BPA) is a refractory pollutant presents in water body that poses serious threats to living organisms. To deal with it, we investigate and evaluate the effectiveness of GO@BiOI/Bi 2 WO 6 composite as a novel photocatalyst for BPA removal from aqueous solutions under UV–vis irradiation. To enhance its removal for BPA, the surface of BiOI/Bi 2 WO 6 is modified with graphene oxide (GO). This composite is named as ‘GO@BiOI/Bi 2 WO 6 ’. Changes in its physico-chemical properties after surface modification with GO are characterized by XRD, FTIR, FESEM-EDS, XPS, PL, and BET methods. Optimized conditions of BPA degradation by the composite are determined under identical conditions. Photodegradation pathways of BPA and its removal mechanisms by the same composite are presented. It is obvious that the GO@BiOI/Bi 2 WO 6 has demonstrated its potential as a promising photocatalyst for BPA removal under UV–vis irradiation. About 81% of BPA removal is attained by the GO@BiOI/Bi 2 WO 6 under optimized conditions (10 mg/L of BPA, 0.5 g/L of dose, pH 7 and 5 h of reaction time). The oxidation by-products of BPA degradation include p -hydroquinone or 4-(1-hydroxy-1-methyl-ethyl)-phenol. In spite of its performance, the treated effluents are still unable to meet the maximum discharge limit of <1 mg/L set by national legislation. Therefore, subsequent biological processes are essential to maximize its biodegradation in the wastewater samples before their discharge into waterbody