Search Results - "Shrivastava, Vimal K"

Transfer Learning-Based Framework for Classification of Pest in Tomato Plants by Pattnaik, Gayatri, Shrivastava, Vimal K., Parvathi, K.

“…Pest in the plant is a major challenge in the agriculture sector. Hence, early and accurate detection and classification of pests could help in precautionary…”
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Exploring the color feature power for psoriasis risk stratification and classification: A data mining paradigm by Shrivastava, Vimal K, Londhe, Narendra D, Sonawane, Rajendra S, Suri, Jasjit S

“…Abstract A large percentage of dermatologist׳s decision in psoriasis disease assessment is based on color. The current computer-aided diagnosis systems for…”
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Analysis of various optimizers on deep convolutional neural network model in the application of hyperspectral remote sensing image classification by Bera, Somenath, Shrivastava, Vimal K.

“…Hyperspectral image (HSI) classification is a most challenging task in hyperspectral remote sensing field due to unique characteristics of HSI data. It…”
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PCA-based Polling Strategy in Machine Learning Framework for Coronary Artery Disease Risk Assessment in Intravascular Ultrasound: A Link between Carotid and Coronary Grayscale Plaque Morphology by Araki, Tadashi, MD, Ikeda, Nobutaka, MD, Shukla, Devarshi, BTech, Jain, Pankaj K., B.E, Londhe, Narendra D., PhD, Shrivastava, Vimal K., M.Tech, Banchhor, Sumit K., MTech, Saba, Luca, MD, Nicolaides, Andrew, PhD, Shafique, Shoaib, MD, Laird, John R., MD, Suri, Jasjit S., PhD, MBA, Fellow AIMBE

“…Highlights • Coronary artery disease risk assessment in intravascular ultrasound. • A link between carotid and coronary grayscale plaque morphology. •…”
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Rice plant disease classification using color features: a machine learning paradigm by Shrivastava, Vimal K., Pradhan, Monoj K.

“…In traditional practices, detection of rice plant diseases by experts is a subjective matter whereas by testing in the laboratory is time-consuming. As a…”
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A novel Parametric Flatten-p Mish activation function based deep CNN model for brain tumor classification by Mondal, Ayan, Shrivastava, Vimal K.

“…The brain tumor is one of the deadliest diseases of all cancers. Influenced by the recent developments of convolutional neural networks (CNNs) in medical…”
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A novel and robust Bayesian approach for segmentation of psoriasis lesions and its risk stratification by Shrivastava, Vimal K., Londhe, Narendra D., Sonawane, Rajendra S., Suri, Jasjit S.

“…•Automatic segmentation of psoriatic lesion using Bayesian model.•Multiclass psoriasis risk assessment system (pRAS).•Implementation of nine pRAS systems which…”
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Computer-aided diagnosis of psoriasis skin images with HOS, texture and color features: A first comparative study of its kind by Shrivastava, Vimal K, Londhe, Narendra D, Sonawane, Rajendra S, Suri, Jasjit S

“…Highlights • Comparative analysis of systems with different feature sets. • HOS features extraction for psoriasis images. • Largest set of mathematical…”
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Reliable and accurate psoriasis disease classification in dermatology images using comprehensive feature space in machine learning paradigm by Shrivastava, Vimal K., Londhe, Narendra D., Sonawane, R.S., Suri, Jasjit S.

“…•CADx system to classify psoriatic lesion and healthy skin in dermatology images.•Integration of grayscale, color, redness and chaotic feature space.•Accurate…”
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Multiclass skin lesion classification using image augmentation technique and transfer learning models by Swetha R, Naga, Shrivastava, Vimal K., Parvathi, K.

“…PurposeThe mortality rate due to skin cancers has been increasing over the past decades. Early detection and treatment of skin cancers can save lives. However,…”
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Swarm intelligence based clustering technique for automated lesion detection and diagnosis of psoriasis by Dash, Manoranjan, Londhe, Narendra D., Ghosh, Subhojit, Shrivastava, Vimal K., Sonawane, Rajendra S.

“…[Display omitted] •Objective analysis of psoriasis disease over a larger dataset of 780 images.•Implementation of swarm intelligence algorithms to obtain…”
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Stroke Risk Stratification and its Validation using Ultrasonic Echolucent Carotid Wall Plaque Morphology: A Machine Learning Paradigm by Araki, Tadashi, Jain, Pankaj K, Suri, Harman S, Londhe, Narendra D, Ikeda, Nobutaka, El-Baz, Ayman, Shrivastava, Vimal K, Saba, Luca, Nicolaides, Andrew, Shafique, Shoaib, Laird, John R, Gupta, Ajay, Suri, Jasjit S

“…Abstract Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has recently been shown to have a promise in classification of…”
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A Kernel-Based Extreme Learning Machine Framework for Classification of Hyperspectral Images Using Active Learning by Pradhan, Monoj K., Minz, Sonajharia, Shrivastava, Vimal K.

“…The rapid development of advanced remote sensing technology with multichannel imaging sensors has increased its potential opportunity in the utilization of…”
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A new method for IVUS-based coronary artery disease risk stratification: A link between coronary & carotid ultrasound plaque burdens by Araki, Tadashi, Ikeda, Nobutaka, Shukla, Devarshi, Londhe, Narendra D, Shrivastava, Vimal K, Banchhor, Sumit K, Saba, Luca, Nicolaides, Andrew, Shafique, Shoaib, Laird, John R, Suri, Jasjit S

“…Highlights • Coronary risk stratification. • Machine learning to link two arteries. • 56 grayscale features. • Coronary tissue characterization. •…”
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First review on psoriasis severity risk stratification: An engineering perspective by Shrivastava, Vimal K, Londhe, Narendra D, Sonawane, Rajendra S, Suri, Jasjit S

“…Abstract Computer-aided diagnosis (CAD) systems have been used for characterization of several dermatologic diseases in the last few years. Psoriasis is a…”
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Reliability analysis of psoriasis decision support system in principal component analysis framework by Shrivastava, Vimal K., Londhe, Narendra D., Sonawane, Rajendra S., Suri, Jasjit S.

“…Reliability and accuracy are essential components in any decision support system. These become even more important with a rising number of features during the…”
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Improved Building Extraction from Remotely Sensed Images by Integration of Encode–Decoder and Edge Enhancement Models by Bera, Somenath, Srivastava, Vandita, Shrivastava, Vimal K.

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Entropy query by bagging-based active learning approach in the extreme learning machine framework for hyperspectral image classification by Pradhan, Monoj K., Minz, Sonajharia, Shrivastava, Vimal K.

“…Active learning (AL) technique is the classification of remote sensing images, where collecting efficient training data is costly in terms of labour and the…”
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RICE PLANT DISEASE CLASSIFICATION USING TRANSFER LEARNING OF DEEP CONVOLUTION NEURAL NETWORK by Shrivastava, V. K., Pradhan, M. K., Minz, S., Thakur, M. P.

“…Early and accurate diagnosis of plant diseases is a vital step in the crop protection system. In traditional practices, identification is performed either by…”
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A novel approach to multiclass psoriasis disease risk stratification: Machine learning paradigm by Shrivastava, Vimal K., Londhe, Narendra D., Sonawane, Rajendra S., Suri, Jasjit S.

“…•Multiclass risk assessment and stratification system for psoriasis disease.•Comparison of four kinds of systems: SVM-PCA, SVM-FDR, DT-PCA and…”
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