Segmentation of Tiles Image Using Various Edge Detection Techniques

Umamaheswari, C.; Bhavani, R.; Sikamani, K. Thirunadana

doi:10.20894/ijdmta.102.004.001.003

Cited by 2 publications

(2 citation statements)

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“…One kernel or mask is rotated by 90 degrees of other. Thus it calculates the value of gradient by using diagonal direction approach.The approximated absolute value of the gradient is shown in the result at each pixel [27].…”

Section: Robert Cross Operatormentioning

confidence: 99%

Hardware Implementation of Sobel Edge Detection Algorithm

Pujare¹,

Sawant²,

Sharma³

et al. 2020

ITM Web Conf.

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In the fields of image processing, feature detection, the edge detection is an important aspect. For detection of sharp changes in the properties of an image, edges are recognized as important factors which provides more information or data regarding the analysis of an image. In this work coding of various edge detection algorithms such as Sobel, Canny, etc. have been done on the MATLAB software, also this work is implemented on the FPGA Nexys 4 DDR board. The results are then displayed on a VGA screen. The implementation of this work using Verilog language of FPGA has been executed on Vivado 18.2 software tool.

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Section: Robert Cross Operatormentioning

confidence: 99%

Hardware Implementation of Sobel Edge Detection Algorithm

Pujare¹,

Sawant²,

Sharma³

et al. 2020

ITM Web Conf.

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“…Machine learning (ML) in drug discovery involves the use of statistical tools for learning and predicting molecular properties including bioactivity [1][2][3]. Popular ML algorithms in this field include Random Forests (RF); [2,5] Naïve Bayesian (NB) [5][6][7][8]; eXtreme Gradient Boosting (XGBoost) [2,9]; K-nearest neighbors (kNN) [2,10]; and probabilistic neural networks (PNN) [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Augmenting bioactivity by docking‐generated multiple ligand poses to enhance machine learning and pharmacophore modelling: discovery of new TTK inhibitors as case study

AL‐Imam,

Daoud,

Hatmal

et al. 2023

Molecular Informatics

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Dual specificity protein kinase threonine/Tyrosine kinase (TTK) is one of the mitotic kinases. High levels of TTK are detected in several types of cancer. Hence, TTK inhibition is considered a promising therapeutic anti‐cancer strategy. In this work, we used multiple docked poses of TTK inhibitors to augment training data for machine learning QSAR modeling. Ligand‐Receptor Contacts Fingerprints and docking scoring values were used as descriptor variables. Escalating docking‐scoring consensus levels were scanned against orthogonal machine learners, and the best learners (Random Forests and XGBoost) were coupled with genetic algorithm and Shapley additive explanations (SHAP) to determine critical descriptors for predicting anti‐TTK bioactivity and for pharmacophore generation. Three successful pharmacophores were deduced and subsequently used for in silico screening against the NCI database. A total of 14 hits were evaluated in vitro for their anti‐TTK bioactivities. One hit of novel chemotype showed reasonable dose‐response curve with experimental IC50 of 1.0 μM. The presented work indicates the validity of data augmentation using multiple docked poses for building successful machine learning models and pharmacophore hypotheses.

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Segmentation of Tiles Image Using Various Edge Detection Techniques

Cited by 2 publications

References 0 publications

Hardware Implementation of Sobel Edge Detection Algorithm

Hardware Implementation of Sobel Edge Detection Algorithm

Augmenting bioactivity by docking‐generated multiple ligand poses to enhance machine learning and pharmacophore modelling: discovery of new TTK inhibitors as case study

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