A novel approach on transform domain watermarking against geometrical deformations

2006 ◽  
Author(s):  
V. Fotopoulos ◽  
A.N. Skodras
Keyword(s):  
Transform Domain ◽  
Novel Approach

scholarly journals Sparse Approach in Filtering of Color Images Corrupted by Mixture Noises

2020 ◽  
Vol 16 ◽  
Keyword(s):  
Noise Suppression ◽  
Impulsive Noise ◽  
Median Filter ◽  
Color Images ◽  
Subjective Perception ◽  
Transform Domain ◽  
Second Stage ◽  
Novel Approach ◽  
Impulsive Noises ◽  
Impulsive Noise Suppression

A novel filtering approach is presented in denoising in the color images contaminated by mixture of additive-impulsive noises. Novel framework consists of three principal stages: impulsive noise suppression that is performed detecting pixels corrupted by impulsive noise and then, filtering found spikes by a variant of median filter; during second stage, original additive noise suppression filter is employed in Wavelet transform domain via a sparse representation and 3D-filtering; finally, nondesirable effects obtained in an image during previous stages are processed to correct fine details. In case of multiplicative noise suppression, the designed denoising scheme uses 3D homomorphic sparse processing stage and post-filtering procedure. Evaluation of novel approach in denoising complex distortions has been performed using objective criteria (PSNR and SSIM measures) and subjective perception via human visual system confirming their better performance in comparison with state-of-theart techniques.

scholarly journals KAT4IA: K-Means Assisted Training for Image Analysis of Field-Grown Plant Phenotypes

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xingche Guo ◽  
Yumou Qiu ◽  
Dan Nettleton ◽  
Cheng-Ting Yeh ◽  
Zihao Zheng ◽  
...  
Keyword(s):  
Plant Traits ◽  
Semisupervised Learning ◽  
Training Data ◽  
Transform Domain ◽  
Neural Network Learning ◽  
Plant Trait ◽  
Novel Approach ◽  
Field Phenotyping ◽  
High Throughput Phenotyping ◽  
Rich Data

High-throughput phenotyping enables the efficient collection of plant trait data at scale. One example involves using imaging systems over key phases of a crop growing season. Although the resulting images provide rich data for statistical analyses of plant phenotypes, image processing for trait extraction is required as a prerequisite. Current methods for trait extraction are mainly based on supervised learning with human labeled data or semisupervised learning with a mixture of human labeled data and unsupervised data. Unfortunately, preparing a sufficiently large training data is both time and labor-intensive. We describe a self-supervised pipeline (KAT4IA) that uses K-means clustering on greenhouse images to construct training data for extracting and analyzing plant traits from an image-based field phenotyping system. The KAT4IA pipeline includes these main steps: self-supervised training set construction, plant segmentation from images of field-grown plants, automatic separation of target plants, calculation of plant traits, and functional curve fitting of the extracted traits. To deal with the challenge of separating target plants from noisy backgrounds in field images, we describe a novel approach using row-cuts and column-cuts on images segmented by transform domain neural network learning, which utilizes plant pixels identified from greenhouse images to train a segmentation model for field images. This approach is efficient and does not require human intervention. Our results show that KAT4IA is able to accurately extract plant pixels and estimate plant heights.

Copper-dependent ATP7B up-regulation drives the resistance of TMEM16A-overexpressing head-and-neck cancer models to platinum toxicity

2019 ◽  
Vol 476 (24) ◽  
pp. 3705-3719 ◽  
Author(s):  
Avani Vyas ◽  
Umamaheswar Duvvuri ◽  
Kirill Kiselyov
Keyword(s):  
Oxidative Stress ◽  
Head And Neck ◽  
Transcriptional Activation ◽  
Platinum Resistance ◽  
Mrna Levels ◽  
Strong Positive Correlation ◽  
Platinum Compounds ◽  
Copper Chelation ◽  
Novel Approach ◽  
Cancer Models

Platinum-containing drugs such as cisplatin and carboplatin are routinely used for the treatment of many solid tumors including squamous cell carcinoma of the head and neck (SCCHN). However, SCCHN resistance to platinum compounds is well documented. The resistance to platinum has been linked to the activity of divalent transporter ATP7B, which pumps platinum from the cytoplasm into lysosomes, decreasing its concentration in the cytoplasm. Several cancer models show increased expression of ATP7B; however, the reason for such an increase is not known. Here we show a strong positive correlation between mRNA levels of TMEM16A and ATP7B in human SCCHN tumors. TMEM16A overexpression and depletion in SCCHN cell lines caused parallel changes in the ATP7B mRNA levels. The ATP7B increase in TMEM16A-overexpressing cells was reversed by suppression of NADPH oxidase 2 (NOX2), by the antioxidant N-Acetyl-Cysteine (NAC) and by copper chelation using cuprizone and bathocuproine sulphonate (BCS). Pretreatment with either chelator significantly increased cisplatin's sensitivity, particularly in the context of TMEM16A overexpression. We propose that increased oxidative stress in TMEM16A-overexpressing cells liberates the chelated copper in the cytoplasm, leading to the transcriptional activation of ATP7B expression. This, in turn, decreases the efficacy of platinum compounds by promoting their vesicular sequestration. We think that such a new explanation of the mechanism of SCCHN tumors’ platinum resistance identifies novel approach to treating these tumors.

Collecting Words: A Clinical Example of a Morphology-Focused Orthographic Intervention

2020 ◽  
Vol 51 (3) ◽  
pp. 544-560 ◽  
Author(s):  
Kimberly A. Murphy ◽  
Emily A. Diehm
Keyword(s):  
Written Language ◽  
Morphological Knowledge ◽  
English Orthography ◽  
Word Level ◽  
Novel Approach ◽  
Language Pathology ◽  
The One ◽  
Critical Intervention ◽  
Reading And Spelling ◽  
Reading And Spelling Difficulties

Purpose Morphological interventions promote gains in morphological knowledge and in other oral and written language skills (e.g., phonological awareness, vocabulary, reading, and spelling), yet we have a limited understanding of critical intervention features. In this clinical focus article, we describe a relatively novel approach to teaching morphology that considers its role as the key organizing principle of English orthography. We also present a clinical example of such an intervention delivered during a summer camp at a university speech and hearing clinic. Method Graduate speech-language pathology students provided a 6-week morphology-focused orthographic intervention to children in first through fourth grade ( n = 10) who demonstrated word-level reading and spelling difficulties. The intervention focused children's attention on morphological families, teaching how morphology is interrelated with phonology and etymology in English orthography. Results Comparing pre- and posttest scores, children demonstrated improvement in reading and/or spelling abilities, with the largest gains observed in spelling affixes within polymorphemic words. Children and their caregivers reacted positively to the intervention. Therefore, data from the camp offer preliminary support for teaching morphology within the context of written words, and the intervention appears to be a feasible approach for simultaneously increasing morphological knowledge, reading, and spelling. Conclusion Children with word-level reading and spelling difficulties may benefit from a morphology-focused orthographic intervention, such as the one described here. Research on the approach is warranted, and clinicians are encouraged to explore its possible effectiveness in their practice. Supplemental Material https://doi.org/10.23641/asha.12290687

Abstract #709: E-Consults: A Novel Approach to Increase Access to Subspecialty Care in Endocrinology

2015 ◽  
Vol 21 ◽  
pp. 128
Author(s):  
Kaniksha Desai ◽  
Halis Akturk ◽  
Ana Maria Chindris ◽  
Shon Meek ◽  
Robert Smallridge ◽  
...  
Keyword(s):  
Novel Approach
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