TRS: Transformers for Remote Sensing Scene Classification

Remote sensing scene classification remains challenging due to the complexity and variety of scenes. With the development of attention-based methods, Convolutional Neural Networks (CNNs) have achieved competitive performance in remote sensing scene classification tasks. As an important method of the attention-based model, the Transformer has achieved great success in the field of natural language processing. Recently, the Transformer has been used for computer vision tasks. However, most existing methods divide the original image into multiple patches and encode the patches as the input of the Transformer, which limits the model’s ability to learn the overall features of the image. In this paper, we propose a new remote sensing scene classification method, Remote Sensing Transformer (TRS), a powerful “pure CNNs→Convolution + Transformer → pure Transformers” structure. First, we integrate self-attention into ResNet in a novel way, using our proposed Multi-Head Self-Attention layer instead of 3 × 3 spatial revolutions in the bottleneck. Then we connect multiple pure Transformer encoders to further improve the representation learning performance completely depending on attention. Finally, we use a linear classifier for classification. We train our model on four public remote sensing scene datasets: UC-Merced, AID, NWPU-RESISC45, and OPTIMAL-31. The experimental results show that TRS exceeds the state-of-the-art methods and achieves higher accuracy.

Efficacy of leeching (Ta‘līq al-‘Alaq) in patients with vitiligo (baras): a comprehensive case study

Vitiligo is a hypomelanotic skin disorder in white patches appear on the skin surface and also involve the hair. The disease is idiopathic, acquired and effects 1-4 percent of the world population. It is belived that there is immunologic influence in the pathogenesis of vitiligo and there is evidence of early cell death in vitiligo melanocytes related to their increased sensitivity to oxidative stress. In Ayurveda the vitiation of three doshas results deraignment of rasa, rakta, mamsa and medadhuta which results in vitiligo patches on skin. In Unani System of Medicine (USM) the deraignment of body humours result in the Fasad-e-Ikhlat which results in the Baras (vitiligo). Since both in Ayurveda and USM leech has been used for various dermatalogicalailments including vitiligo. In this study leeching (hirudotherapy) were done in vitiligo patients of both sexes with single and multiple patches and successful results were observed.

Multi-Descriptor Random Sampling for Patch-Based Face Recognition

While there has been a massive increase in research into face recognition, it remains a challenging problem due to conditions present in real life. This paper focuses on the inherently present issue of partial occlusion distortions in real face recognition applications. We propose an approach to tackle this problem. First, face images are divided into multiple patches before local descriptors of Local Binary Patterns and Histograms of Oriented Gradients are applied on each patch. Next, the resulting histograms are concatenated, and their dimensionality is then reduced using Kernel Principle Component Analysis. Once completed, patches are randomly selected using the concept of random sampling to finally construct several sub-Support Vector Machine classifiers. The results obtained from these sub-classifiers are combined to generate the final recognition outcome. Experimental results based on the AR face database and the Extended Yale B database show the effectiveness of our proposed technique.

Primary Cutaneous Extranodal NK/T Cell Lymphoma (Nasal Type): A Case Report and Review of Literatures

A case of extranodal NK/T cell lymphoma (nasal type) with skin lesion as the first manifestation is reported. A 82 year old female presented with fever for 10 days, and mass with ulceration on right shoulder for 4 days. Clinically, a walnut-sized red mass with local ulceration and scab can be seen on the right shoulder. Part of the lesion had rupture scab. A circular-like infiltrated dark red plaque with a diameter of about 4cm can be seen on the right chest, with yellow and white dry secretion in the center. Multiple patches of dark red spots from coins to walnuts can be seen on the trunk and limbs. Based on skin lesions, histological, immunohistochemical staining and EBER in situ hybridization, a diagnose of primary cutaneous extranodal NK/T cell lymphoma, nasal type was made.

Characterization of Color Differences for Color Palettes

Various color difference metrics were developed for characterizing the perceived color difference between individual color patches. Color difference between palettes containing multiple color patches, however, is critically important in product design and computer graphics. This study aimed to investigate how the perceived color difference between a pair of color palettes containing more than a single color patch is affected by the order and number of color patches in the palette. Two reference color sets were generated and each set had four color palettes containing 1, 4, 9, and 16 color patches that were arranged as 1 × 1, 2 × 2, 3 × 3, and 4 × 4 patterns. Human observers scaled the color differences between a color palette of the reference set and a color palette that had revised colors, or revised orders, or a combination of revised colors and orders compared to the reference palette. The calculated color differences between the two palettes were derived using the Minimum Color Difference Model (MICDM) algorithm proposed in a recent work with different color difference metrics, including CIELAB, CMC, CIE94, and DE2000. It was found that the perceived color differences of pairs of individual color patches were significantly larger than those containing multiple patches, when the calculated color differences were the same. The color differences metrics, except for CIE94, had similar performance when characterizing perceived color differences between color palettes.

Clinical efficacy of Unani formulations in psoriasis (Da-us-Sadaf): a case report

<p>A seven-year-old male child suffering from multiple patches over the scalp with severe burning, pain, and scaly skin, came for treatment in government Unani dispensary, Majajpur, Bharatpur, Rajasthan, India. The patient has lesions and erythema with some papules over the nape of the neck. After the proper history, physical examination, positive auspitz sign, candle grease sign and grattage test he was diagnosed as a patient of scalp psoriasis. The patient was treated with Unani drugs; sharbat murakkab musaffi khoon, arq shahatra and marham safed kafoori to evaluate the efficacy of drugs and to avoid any side effects and recurrence of the disease. The patient showed excellent and admirable results within 90 days of treatment and marked remission was found in all features without any side effect, recurrence and complications.</p>

A Feature Integrated Saliency Estimation Model for Omnidirectional Immersive Images

Omnidirectional, or 360°, cameras are able to capture the surrounding space, thus providing an immersive experience when the acquired data is viewed using head mounted displays. Such an immersive experience inherently generates an illusion of being in a virtual environment. The popularity of 360° media has been growing in recent years. However, due to the large amount of data, processing and transmission pose several challenges. To this aim, efforts are being devoted to the identification of regions that can be used for compressing 360° images while guaranteeing the immersive feeling. In this contribution, we present a saliency estimation model that considers the spherical properties of the images. The proposed approach first divides the 360° image into multiple patches that replicate the positions (viewports) looked at by a subject while viewing a 360° image using a head mounted display. Next, a set of low-level features able to depict various properties of an image scene is extracted from each patch. The extracted features are combined to estimate the 360° saliency map. Finally, bias induced during image exploration and illumination variation is fine-tuned for estimating the final saliency map. The proposed method is evaluated using a benchmark 360° image dataset and is compared with two baselines and eight state-of-the-art approaches for saliency estimation. The obtained results show that the proposed model outperforms existing saliency estimation models.