Browsing Electronics by Author "Lanjewar, M."

Now showing items 1-13 of 13

Backpropagation neural network-based machine learning model for prediction of blood urea and glucose in CKD patients

Parab, J.S.; Sequeira, M.; Lanjewar, M.; Pinto, C.; Naik, G.M. (IEEE Journal of Translational Engineering in Health and Medicine. 9; 2021; ArticleID_4900608.)

Diabetes mellitus and its complication such as heart disease, stroke, kidney failure, etc. is a serious concern all over the world. Hence, monitoring some important blood parameters non-invasively is of utmost importance, ...
Cloud-based COVID-19 disease prediction system from X-Ray images using convolutional neural network on smartphone

Lanjewar, M.; Shaikh, A.Y.; Parab, J.S. (Multimedia Tools and Applications. 82(19); 2023; 29883-29912.)

COVID-19 has engulfed over 200 nations through human-to-human transmission, either directly or indirectly. Reverse Transcription-polymerase Chain Reaction (RT-PCR) has been endorsed as a standard COVID-19 diagnostic procedure ...
CNN and transfer learning methods with augmentation for citrus leaf diseases detection using PaaS cloud on mobile

Lanjewar, M.; Parab, J.S. (Multimedia Tools and Applications. NYP; 2023; NYP.)

Leaf and fruit infections are the primary cause of the maximum harm to the crop, which decreases the quality and amount of the goods. To improve the productivity of plants, the timely identification of the infection is ...
CNN with machine learning approaches using ExtraTreesClassifier and MRMR feature selection techniques to detect liver diseases on cloud

Lanjewar, M.; Parab, J.S.; Shaikh, A.Y.; Sequeira, M. (Cluster Computing. 26(6); 2022; 3657-3672.)

Liver disease is a significant global burden on health, with about a few hundred million people suffering from chronic liver disease (CLD), with approximately 2 million deaths each year. Liver diseases are tough to identify ...
Convolutional Neural Networks based classifications of soil images

Lanjewar, M.; Gurav, O.L. (Multimedia Tools and Applications. 81(7); 2022; 10313-10336.)

The utilization of Artificial Intelligence (AI) and Machine Learning(ML) in the image processing domain is useful to detect and recognize the types of soil. The main aim of the present work is to process the soil images ...
Detection of tartrazine colored rice flour adulteration in turmeric from multi-spectral images on smartphone using convolutional neural network deployed on PaaS cloud

Lanjewar, M.; Parab, J.S.; Morajkar, P.P. (Multimedia Tools and Applications. 81(12); 2022; 16537-16562.)

Food adulteration occurs globally, in many facets, and affects almost all food commodities. Adulteration is not just a crucial economic problem, but it may also lead to serious health problems for consumers. Turmeric ...
Development of framework by combining CNN with KNN to detect Alzheimer's disease using MRI images

Lanjewar, M.; Parab, J.S.; Shaikh, A.Y. (Multimedia Tools and Applications. 82(8); 2023; 12699-12717.)

Alzheimer's disease (AD) is an irremediable, irrecoverable brain illness without proper treatment. Therefore, AD recognition is essential for precluding and dominating its advancement. The conventional method considers the ...
FoG and Cloud Computing with Jetson Nano (Chapter 5)

Parab, J.S.; Lanjewar, M.; Sequeira, M.; Naik, G.M.; Shaikh, A.Y. (Python Programming Recipes for IoT Applications, Part of the Transactions on Computer Systems and Networks book series (TCSN). 2023; 123-166.)

FoG and cloud paradigms are helping the IoT devices to offload the computing in order to reduce power consumption and increase battery life. The Jetson Nano SBC is an exciting platform which can act as a FoG node and as ...
Hybrid method for accurate starch estimation in adulterated turmeric using Vis-NIR spectroscopy

Lanjewar, M.; Morajkar, P.P.; Parab, J.S. (Food Additives & Contaminants: Part A. 40(9); 2023; 1131-1146.)

Turmeric is widely used as a health supplement and foodstuff in South East Asian countries because of its medicinal benefits. Like several other plants and peppers, turmeric is prone to exploitation because of its economic ...
Lung cancer detection from CT scans using modified DenseNet with feature selection methods and ML classifiers

Lanjewar, M.; Panchbhai, K.G.; Charanarur P. (Expert Systems with Applications. 224; 2023; ArticleID_119961.)

Lung cancer is a highly life-threatening disease worldwide, and detection is crucial. In this study, the Kaggle chest CT-scan images dataset was used to identify lung cancer in four categories: adenocarcinoma, large cell ...
Machine learning based technique to predict the water adulterant in milk using portable near infrared spectroscopy

Lanjewar, M.; Parab, J.S.; Kamat, R.K. (Journal of Food Composition and Analysis. 131; 2024; ArticleID_106270.)

Milk adulteration is a significant problem globally, as it is the most widely consumed and essential food product. Due to this, monitoring milk quality is necessary for sustaining human health. A Machine Learning (ML) based ...
Portable system to detect starch adulteration in turmeric using NIR spectroscopy

Lanjewar, M.; Morajkar, P.P.; Parab, J.S. (Food Control. 155; 2024; ArticleID_110095.)

Analytical tests are commonly performed in laboratories to analyze and ensure food quality due to concerns about food adulteration. However, traditional analytical methods that rely on chemicals or equipment are often ...
Python Programming Recipes for IoT Applications

Parab, J.S.; Lanjewar, M.; Sequeira, M.; Naik, G.M.; Shaikh, A.Y. (Springer Nature. 2023; 192pp.)

Now showing items 1-13 of 13

Search IR

Advanced Search

Browse

All of IR
This Collection
- By Issue Date
- Authors
- Titles
- Subjects

Browsing Electronics by Author "Lanjewar, M."

Browsing Electronics by Author "Lanjewar, M."

Search IR

Browse

All of IR

This Collection

My Account