Invariant Jordan curves of Sierpiski carpet rational maps

In this paper, we prove that if $R\colon\widehat{\mathbb{C}}\to\widehat{\mathbb{C}}$ is a postcritically finite rational map with Julia set homeomorphic to the Sierpi\'nski carpet, then there is an integer $n_0$, such that, for any $n\ge n_0$, there exists an $R^n$-invariant Jordan curve $\Gamma$ containing the postcritical set of $R$.Comment: 16 pages, 1 figu

Rough Fuzzy Distance of the Rough Fuzzy Number

Rough sets theory and fuzzy sets theory research the unperfect problem in information systems. the combination of them formed Rough fuzzy sets and Rough Fuzzy number. in this paper, defines the Rough fuzzy distance of the Rough fuzzy number. Then it discusses the nature of Rough fuzzy distance.Key words: Rough fuzzy number; Distance; Rough fuzzy Distanc

An oil painters recognition method based on cluster multiple kernel learning algorithm

A lot of image processing research works focus on natural images, such as in classification, clustering, and the research on the recognition of artworks (such as oil paintings), from feature extraction to classifier design, is relatively few. This paper focuses on oil painter recognition and tries to find the mobile application to recognize the painter. This paper proposes a cluster multiple kernel learning algorithm, which extracts oil painting features from three aspects: color, texture, and spatial layout, and generates multiple candidate kernels with different kernel functions. With the results of clustering numerous candidate kernels, we selected the sub-kernels with better classification performance, and use the traditional multiple kernel learning algorithm to carry out the multi-feature fusion classification. The algorithm achieves a better result on the Painting91 than using traditional multiple kernel learning directly

Transformer-based No-Reference Image Quality Assessment via Supervised Contrastive Learning

Image Quality Assessment (IQA) has long been a research hotspot in the field of image processing, especially No-Reference Image Quality Assessment (NR-IQA). Due to the powerful feature extraction ability, existing Convolution Neural Network (CNN) and Transformers based NR-IQA methods have achieved considerable progress. However, they still exhibit limited capability when facing unknown authentic distortion datasets. To further improve NR-IQA performance, in this paper, a novel supervised contrastive learning (SCL) and Transformer-based NR-IQA model SaTQA is proposed. We first train a model on a large-scale synthetic dataset by SCL (no image subjective score is required) to extract degradation features of images with various distortion types and levels. To further extract distortion information from images, we propose a backbone network incorporating the Multi-Stream Block (MSB) by combining the CNN inductive bias and Transformer long-term dependence modeling capability. Finally, we propose the Patch Attention Block (PAB) to obtain the final distorted image quality score by fusing the degradation features learned from contrastive learning with the perceptual distortion information extracted by the backbone network. Experimental results on seven standard IQA datasets show that SaTQA outperforms the state-of-the-art methods for both synthetic and authentic datasets. Code is available at https://github.com/I2-Multimedia-Lab/SaTQAComment: Accepted by AAAI2

Effect of the oxygen flow on the properties of ITO thin films deposited by ion beam assisted deposition (IBAD)

ITO films were deposited onto glass substrates by ion beam assisted deposition method. The oxygen ions were produced using a Kaufman ion source. The oxygen flow was varied from 20 until 60 sccm and the effect of the oxygen flow on properties of ITO films has been studied. The structural properties of the film were characterized by X-ray diffraction and atomic force microscopy. The optical properties were characterized by optical transmission measurements and the optical constants (refractive index n and extinction coefficient k) and film thickness have been obtained by fitting the transmittance using a semi-quantum model. The electrical properties were characterized by Hall effect measurements. It has been found that the ITO film with low electrical resistivity and high transmittance can be obtained with 40 sccm oxygen flow (the working pressure is about 2.3 × 10−2 Pa at this oxygen flow).Fundação para a Ciência e a Tecnologia (FCT) - SFRH-BSAB-514