Log in

Relevant bibliographies by topics / Flask deployment / Journal articles

To see the other types of publications on this topic, follow the link: Flask deployment.

Journal articles on the topic 'Flask deployment'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Flask deployment.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Karion, A., C. Sweeney, S. Wolter, et al. "Long-term greenhouse gas measurements from aircraft." Atmospheric Measurement Techniques Discussions 5, no. 5 (2012): 7341–82. http://dx.doi.org/10.5194/amtd-5-7341-2012.

Full text

Abstract:

Abstract. In March 2009 the NOAA/ESRL/GMD Carbon Cycle and Greenhouse Gases Group collaborated with the US Coast Guard (USCG) to establish the Alaska Coast Guard (ACG) sampling site, a unique addition to NOAA's atmospheric monitoring network. This collaboration takes advantage of USCG bi-weekly Arctic Domain Awareness (ADA) flights, conducted with Hercules C-130 aircraft from March to November each year. NOAA has installed window-replacement inlet plates on two USCG C-130 aircraft and deploys a pallet with NOAA instrumentation on each ADA flight. Flights typically last 8 h and cover a very lar

APA, Harvard, Vancouver, ISO, and other styles

2

Dani, Himangi. "Review on Frameworks Used for Deployment of Machine Learning Model." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (2022): 211–15. http://dx.doi.org/10.22214/ijraset.2022.40222.

Full text

Abstract:

Abstract: According to the current scenario, the use of machine learning is increasing in a variety of web applications and services. A good visual experience, fast performance, and easy to use framework is critical for developing and deploying your model. Working on a machine learning model is one thing but deploying a machine learning model to production can be another. Creating a Machine Learning model is one thing but deploying the model in real-time is the real challenge. For that purpose, many different technologies are available in the field. The simplest way to deploy a machine learnin

APA, Harvard, Vancouver, ISO, and other styles

3

Hidayatullah Nuriadi, Siti, Erlin Sabri, Alyauma Hajjah, and Ramalia Noratama Putri. "Soursop Leaf Disease Detection With CNNs: From Training to Deployment." INOVTEK Polbeng - Seri Informatika 10, no. 2 (2025): 1185–96. https://doi.org/10.35314/sn8avr92.

Full text

Abstract:

Soursop (Annona muricata) is a valuable tropical fruit crop that is highly susceptible to leaf diseases caused by fungal, bacterial, and viral infections. These diseases can significantly impact crop yield and quality, posing challenges for farmers, especially when early detection is delayed. This study proposes an automated solution using Convolutional Neural Networks (CNNs) to detect soursop leaf diseases through image classification. A dataset of 400 labelled leaf images, including healthy and diseased leaves (Leaf Rust, Leaf Spot, and Sooty Mold), was collected and preprocessed for the dat

APA, Harvard, Vancouver, ISO, and other styles

4

Ramadhani, Adnin, and Abu Salam. "Deployment of Web-Based YOLO for CT Scan Kidney Stone Detection." sinkron 8, no. 3 (2024): 1357–68. http://dx.doi.org/10.33395/sinkron.v8i3.13744.

Full text

Abstract:

This research aims to develop a kidney stone object detection system using machine learning techniques like YOLO and object detection, integrated into a Flask-based web interface to support early diagnosis by medical professionals. The trained model demonstrates strong pattern learning capabilities. Evaluation of the public dataset model reveals an average mean Average Precision (mAP) of 0.9698 for 'kidney stone' labels. This detection model exhibits high performance with an accuracy rate of 96.33%, precision of 96.98%, recall of 99.23%, and an F1-score of 98.1%. Clinical data evaluation shows

APA, Harvard, Vancouver, ISO, and other styles

5

DURGA RAO, JONNADULA, and M. NAGA KEERTHI. "Predicting Prices of Used Cars with Python and ML." International Scientific Journal of Engineering and Management 04, no. 07 (2025): 1–9. https://doi.org/10.55041/isjem04748.

Full text

Abstract:

This project presents a comprehensive machine learning-based web application designed to predict prices of used cars using Python. The system begins with data preparation, where a cleaned dataset is ingested and structured with key automotive features such as brand, model, year, fuel type, and kilometres driven. The data undergoes preprocessing and feature selection to ensure optimal input for a regression model. A Linear Regression model trained on historical car listings is used to predict prices based on user inputs. The model’s performance is evaluated using standard metrics like R-squared

APA, Harvard, Vancouver, ISO, and other styles

6

Jyoti Singh. "Web Application Development and Cybersecurity: Integrating APIs, Logging, and Defense Mechanisms." Panamerican Mathematical Journal 35, no. 1 (2024): 199–207. https://doi.org/10.52783/pmj.v35.i1.5049.

Full text

Abstract:

This project presents the development of a web application using Flask, incorporating APIs for address and weather information retrieval, and implementing cybersecurity defense mechanisms. The front-end comprises HTML templates stylized with CSS, while the back-end integrates Flask to handle form submissions and API calls. The system caches data for improved performance. To ensure security, measures like logging, honeypot deployment, and iptable rules were used to mitigate unauthorized access. The evaluation involved usability testing, service enumeration using Nmap and Gobuster, and vulnerabi

APA, Harvard, Vancouver, ISO, and other styles

7

Dutta, Srijeeta, Priyanshu Pal, Priyanjana Das, Puja Hore Borsha, and Trisha Bera. "CREDIT CARD FRAUD DETECTION USING MACHINE LEARNING AND DEPLOYMENT USING FLASK." International Journal of Computer Science and Mobile Computing 13, no. 5 (2024): 71–75. http://dx.doi.org/10.47760/ijcsmc.2024.v13i05.006.

Full text

Abstract:

Credit card fraud detection is a method which is design in such a way where fraudulent transactions can be identified with different algorithms present in the system. As, due to the presence of such a software, it would be easy for all to know the transactions occur that are legit or fraudulent in that particular credit card. The different algorithms which are being used are Random Forest Algorithm, Support Vector Machine and Isolation Forest Algorithm. The data is stored in the dataset for a temporary time till the software runs, once the software restarts the data will be lost. The future sc

APA, Harvard, Vancouver, ISO, and other styles

8

Karion, A., C. Sweeney, S. Wolter, et al. "Long-term greenhouse gas measurements from aircraft." Atmospheric Measurement Techniques 6, no. 3 (2013): 511–26. http://dx.doi.org/10.5194/amt-6-511-2013.

Full text

Abstract:

Abstract. In March 2009 the NOAA/ESRL/GMD Carbon Cycle and Greenhouse Gases Group collaborated with the US Coast Guard (USCG) to establish the Alaska Coast Guard (ACG) sampling site, a unique addition to NOAA's atmospheric monitoring network. This collaboration takes advantage of USCG bi-weekly Arctic Domain Awareness (ADA) flights, conducted with Hercules C-130 aircraft from March to November each year. Flights typically last 8 h and cover a large area, traveling from Kodiak up to Barrow, Alaska, with altitude profiles near the coast and in the interior. NOAA instrumentation on each flight in

APA, Harvard, Vancouver, ISO, and other styles

9

Premlal, Nenavath. "Predictive Farming: Harnessing Data and AI for Smarter, Sustainable Agriculture." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41392.

Full text

Abstract:

Predictive Farming: Harnessing Data and AI for Smarter, Sustainable Agriculture leverages advanced technologies to enhance agricultural productivity, sustainability, and efficiency. This research focuses on developing a predictive farming system powered by machine learning models to optimize crop management and yield prediction. The project integrates a web-based interface using Flask- based backend for machine learning model deployment. The system analyzes agricultural data to provide insights on crop health, soil conditions, and optimal farming practices. The results demonstrate improved dec

APA, Harvard, Vancouver, ISO, and other styles

10

Ekmalle, Mr Abhiraj. "“Conversational AI for Customer Support”." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04356.

Full text

Abstract:

ABSTRACT: This research paper presents a web-based Conversational AI system developed for enhancing customer support services using Natural Language Processing (NLP), Machine Learning (ML), and Flask for deployment. The system is designed to simulate human-like conversation, resolve customer queries, and operate 24/7 without human intervention. By leveraging intelligent dialogue management and intent recognition, the system can handle frequently asked questions, route complex queries, and significantly reduce human workload. This work demonstrates the integration of AI-driven models within a l

APA, Harvard, Vancouver, ISO, and other styles

11

Kahingide, Hastyantoko Dwiki, and Abu Salam. "Deployment of Kidney Tumor Disease Object Detection Using CT-Scan with YOLOv5." Journal of Applied Informatics and Computing 8, no. 1 (2024): 98–105. http://dx.doi.org/10.30871/jaic.v8i1.7771.

Full text

Abstract:

Image processing plays a crucial role in identifying kidney tumors through CT-Scan images. Object detection technology, particularly YOLO, stands out for its speed and accuracy in facilitating more detailed analysis. Using Flask as a web framework offers optimal responsiveness, providing adaptive ease of use, especially in medical image processing. Evaluation of the model shows impressive results, with a mean Average Precision (mAP) of 0.987 for the 'kidney tumor' label. Detection on public data demonstrated high performance with accuracy, precision, recall, and F1-Score of 98.56%, 98.66%, 99.

APA, Harvard, Vancouver, ISO, and other styles

12

Santosh Kumar, Mohammad Faisal. "Implementation and Validation of a Digital Privacy Framework for Crowdsourced IoT Data Processing." Journal of Information Systems Engineering and Management 10, no. 21s (2025): 890–98. https://doi.org/10.52783/jisem.v10i21s.3453.

Full text

Abstract:

The proposed privacy-preserving crowdsourcing framework integrates IoT-based anomaly detection with differential privacy, homomorphic encryption, and federated learning. The framework protects data gathering, anonymization, and processing while ensuring accurate outcomes. The framework is built using Flask and Isolation Forest, which ensures the balance between utility and privacy while providing security for crowdsourced IoT applications for real-world deployment.

APA, Harvard, Vancouver, ISO, and other styles

13

Dr., Juby Mathew, Sen Easow Neil, Shankar Rajalakshmi, Babu Nandhu, and Pratap Singh Rudra. "Career Finder: AI powered career guider." International Journal on Emerging Research Areas (IJERA) 05, no. 01 (2025): 174–77. https://doi.org/10.5281/zenodo.15187120.

Full text

Abstract:

This paper discusses the overall design, development, and deployment of an AI-based career recommendation system, organized into four interdependent modules: User Interface (UI) Design and Development, Backend Development and API Management, AI Model Integration and Recommendation Engine, and Database and Deployment. The platform leverages cutting-edge technologies such as React.js for a dynamic front-end, Flask for robust backend API development, OpenAI GPT-based models (or alternatives like Hugging Face Transformers or LLaMA) for personalized career insights, and MongoDB for scalable da

APA, Harvard, Vancouver, ISO, and other styles

14

K Venkateswara Rao. "Leveraging Flask API and Machine Learning to Forecast Multiple Diseases." Communications on Applied Nonlinear Analysis 32, no. 1s (2024): 150–62. http://dx.doi.org/10.52783/cana.v32.2145.

Full text

Abstract:

The study described in this abstract used machine learning to predict several diseases, and it integrated the model into a Flask API. A user-friendly platform for disease prediction based on patient symptoms and medical history was the goal of the paper. A number of strategies were used to optimize the predictive performance once the machine learning model had been trained on a sizable dataset of patient records. The model was made accessible as a web service through the usage of the Flask API, enabling simple deployment and integration into current healthcare systems. The study's findings dem

APA, Harvard, Vancouver, ISO, and other styles

15

Revathy, S. P., R. Srimathi, and H. Yuvapriya. "Document Similarity Analysis and Template Matching in Health Insurance Using Python Flask." June 2024 6, no. 2 (2024): 179–90. http://dx.doi.org/10.36548/jitdw.2024.2.006.

Full text

Abstract:

In recent days, a primary challenge faced by healthcare insurance organizations is the reliance on a large number of files to process insurance claims and make coverage decisions. With the gradual increase in medical insurance in India, the number of people buying medical insurance plans is rising. Document processing plays a pivotal role in the efficient management of health insurance policies and claims. This proposed study presents an innovative approach to document template matching specifically tailored for the health insurance domain, implemented using the Python Flask web framework. Int

APA, Harvard, Vancouver, ISO, and other styles

16

Vrinda Khandelwal, Anjali Arora, and Roshni Kapoor. "Tomato Leaf Disease Detection Using CNN and Web Deployment Via Flask and Ngrok." International Research Journal on Advanced Engineering and Management (IRJAEM) 3, no. 07 (2025): 2371–76. https://doi.org/10.47392/irjaem.2025.0374.

Full text

Abstract:

Tomato plants are heavily susceptible to a range of diseases that bring about major damage to crops in agriculture. Early detection and classification of these diseases are crucial for crop maintenance and conservation of production. This paper proposes a Convolutional Neural Network (CNN)-based multi-class classification for tomato leaf diseases. The model is trained on an open-source dataset and is deployed via a Flask web application, accessed using Ngok. The system provides real-time disease prediction based on user-uploaded images and provides specific remedies for each identified disease

APA, Harvard, Vancouver, ISO, and other styles

17

Joshy, Ms S. Agnes, and S. Karthika. "Rainfall Prediction Using Machine Learning with Web Deployment." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–7. https://doi.org/10.55041/ijsrem43869.

Full text

Abstract:

Rainfall prediction plays a crucial role in agriculture, disaster management, and water resource planning. Traditional forecasting methods rely on statistical techniques, which may not effectively capture the complex patterns of weather data. This project utilizes machine learning (ML) techniques to enhance the accuracy of rainfall prediction. Various ML algorithms such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks are employed to analyse historical weather data, including temperature, humidity, wind speed, and atmospheric pressure. The proposed system preproce

APA, Harvard, Vancouver, ISO, and other styles

18

Panduri, Bharathi, P. K. Abhilash, Chidananda K., Venkata Naga Tejaswi Bethapud, Anjali Naudiyal, and Mahitha Kodamunja. "An efficient and sustainable novel approach for prediction of start-up company success rates through sustainable machine learning paradigms." E3S Web of Conferences 430 (2023): 01086. http://dx.doi.org/10.1051/e3sconf/202343001086.

Full text

Abstract:

The primary objective is to construct a sustainable machine-learning model that utilizes multiple variables to forecast the success of a startup enterprise. It incorporates a Flask application for creating a user-friendly interface, where users can input specific parameters related to a startup, such as financial metrics, industry sector, and location. These inputs are then passed through a sustainable machine learning prediction model, which has been trained on a comprehensive dataset of startup information. The model employs sustainable advanced algorithms to evaluate their startup ventures'

APA, Harvard, Vancouver, ISO, and other styles

19

Manjushree, Nayak, and Panda Subhakanta. "Online Grocery Recommendation System Implementation Using Python Flask and Machine Learning." Advancement in Image Processing and Pattern Recognition 7, no. 2 (2024): 78–85. https://doi.org/10.5281/zenodo.10715185.

Full text

Abstract:

<em>This paper describes the creation and deployment of a sophisticated online grocery recommendation system that makes use of machine learning techniques using Python Flask. E-commerce is growing at an exponential rate, and this is especially true for the food industry. To improve consumer satisfaction, personalised and effective recommendation systems are essential. The suggested method makes use of cutting-edge machine learning techniques to examine past data, user preferences, and in-the-moment interactions in order to provide precise and customised grocery recommendations. The web framewo

APA, Harvard, Vancouver, ISO, and other styles

20

Dixit, Puneet, Chaitanya Andhale, and Sumit Jaiswar. "Fruit Disease Detection using VGG16 and Flask: A Deep Learning-Based Web Application for Precision Agriculture." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 3527–31. https://doi.org/10.22214/ijraset.2025.68132.

Full text

Abstract:

Abstract: Fruit diseases such as apple scab, tomato bacterial spot, and mango anthracnose significantly affect agricultural productivity, particularly for high-value crops like apples, tomatoes, and mangoes. These diseases can result in considerable yield losses if not identified and managed promptly. This study introduces a deep learning-based solution using the VGG16 convolutional neural network (CNN) to detect these diseases, achieving validation accuracies above 90% across all tested fruits. The trained models were seamlessly integrated into a Flask web application, enabling real-time dise

APA, Harvard, Vancouver, ISO, and other styles

21

Kumar Sah, Abishek. "A Multilingual AI Chatbot for Real-Time College Admission Enquiries using Web Scraping and Natural Language Processing." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–7. https://doi.org/10.55041/isjem03503.

Full text

Abstract:

Abstract—In order to meet the increasing demand for clear and reliable information about college admissions, this study proposes the creation and deployment of an AI-powered chatbot that operates online. The constraints of static databases are removed by the suggested solution, which uses web scraping and Google search to dynamically extract real-time data from the internet. Using sophisticated natural language processing (NLP) techniques, the chatbot integrates multilingual support for Hindi and English. Intelligent query handling, automatic translation, and language detection are essential e

APA, Harvard, Vancouver, ISO, and other styles

22

Dev, Sambhav. "Leveraging Transfer Learning in Deep Convolutional Neural Networks for Pneumonia Diagnosis from Chest X-Rays." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49934.

Full text

Abstract:

Abstract—Pneumonia is a major worldwide health concern, particularly in areas of limited access to healthcare, causing considerable morbidity and mortality. Standard diagnosis is based on human interpretation of chest radiographs, a time- and labor-consuming task with variability and potential for errors. Deep learning, especially Convolutional Neural Networks (CNNs), has shown promise in computer-aided medical image analysis. This paper proposes a transfer learning-based CNN model for pneumonia detection, employing pre-trained architectures to achieve accuracy and handle data sparsity. The mo

APA, Harvard, Vancouver, ISO, and other styles

23

Kamakshi Thai, P. "Fabric Defect Highlighting using Machine Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46645.

Full text

Abstract:

ABSTRACT Quality inspection is crucial in textile manufacturing, but traditional manual methods are slow, inconsistent, and prone to human error. To address these challenges, this project proposes an automated fabric defect detection system using computer vision and machine learning. The system identifies defects such as holes, stains and uneven weaves through image analysis. It leverages OpenCV for image processing and Support Vector Machines (SVMs) for defect classification. Deployment through Flask or Streamlit enables easy application access, while real-time camera integration supports imm

APA, Harvard, Vancouver, ISO, and other styles

24

G.K.Ramakrishna and Dr.B.Mahesh. "Real-Time Object Detection using Yolov9c and Flask Web Application." international journal of engineering technology and management sciences 9, no. 2 (2025): 699–703. https://doi.org/10.46647/ijetms.2025.v09i02.089.

Full text

Abstract:

Deep learning is widely used for advanced applications of image and video processing with highperformance levels. Deep learning neural networks make use of the higher levels of accuracy inprediction and dynamic data analysis. Deep neural network has shown its extraordinaryperformance in different task of computer vision and machine learning tasks. These types ofnetworks often require large sets of labeled data for training and involve high computationalcomplexity. This poses considerable challenges for the development and deployment of deep neuralnetworks in realtime systems. In The proposed r

APA, Harvard, Vancouver, ISO, and other styles

25

Pattansheetti, Kedar. "Scalable Parking Management Using Cloud Infrastructure and Devops." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 218–22. https://doi.org/10.22214/ijraset.2025.69962.

Full text

Abstract:

Parking management has become a critical issue in modern urban areas due to the increasing number of vehicles. Traditional parking methods rely heavily on manual intervention, leading to inefficiencies, congestion, and high operational costs. To address these challenges, this research proposes a cloud-based Parking Management System that integrates DevOps automation tools to ensure efficiency, scalability, and real-time monitoring. The system is developed using Flask, MySQL, HTML, CSS, and JavaScript and is hosted on AWS EC2 (Free Tier). It employs DevOps tools like Git, Jenkins, and Docker fo

APA, Harvard, Vancouver, ISO, and other styles

26

Udhika, Meghana Kotha, Gaddam Haveela, Reddy Siddenki Deepthi, and Saleti Sumalatha. "A comparison of various machine learning algorithms and execution of flask deployment on essay grading." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 3 (2023): 2990–98. https://doi.org/10.11591/ijece.v13i3.pp2990-2998.

Full text

Abstract:

Students’ performance can be assessed based on grading the answers written by the students during their examination. Currently, students are assessed manually by the teachers. This is a cumbersome task due to an increase in the student-teacher ratio. Moreover, due to coronavirus disease (COVID-19) pandemic, most of the educational institutions have adopted online teaching and assessment. To measure the learning ability of a student, we need to assess them. The current grading system works well for multiple choice questions, but there is no grading system for evaluating the essays. In thi

APA, Harvard, Vancouver, ISO, and other styles

27

Kotha, Udhika Meghana, Haveela Gaddam, Deepthi Reddy Siddenki, and Sumalatha Saleti. "A comparison of various machine learning algorithms and execution of flask deployment on essay grading." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 3 (2023): 2990. http://dx.doi.org/10.11591/ijece.v13i3.pp2990-2998.

Full text

Abstract:

<p><span lang="EN-US">Students’ performance can be assessed based on grading the answers written by the students during their examination. Currently, students are assessed manually by the teachers. This is a cumbersome task due to an increase in the student-teacher ratio. Moreover, due to coronavirus disease (COVID-19) pandemic, most of the educational institutions have adopted online teaching and assessment. To measure the learning ability of a student, we need to assess them. The current grading system works well for multiple choice questions, but there is no grading system for e

APA, Harvard, Vancouver, ISO, and other styles

28

Hatami, Muhammad, Tukino Tukino, Fitria Nurapriani, Widiyawati Widiyawati, and Wresti Andriani. "DETEKSI HELMET DAN VEST KESELAMATAN SECARA REALTIME MENGGUNAKAN METODE YOLO BERBASIS WEB FLASK." EDUSAINTEK: Jurnal Pendidikan, Sains dan Teknologi 10, no. 1 (2023): 221–33. http://dx.doi.org/10.47668/edusaintek.v10i1.651.

Full text

Abstract:

Menurut ILO, setiap tahun ada lebih dari 250 juta kecelakaan di tempat kerja. Penyebab kecelakaan sebanyak 80% dikarenakan kelalaian yang dilakukan oleh pekerja yaitu perilaku tidak aman seperti tidak memakai APD. Perlunya pengawasan terhadap pekerja merupakan hal penting dalam mengurangi kecelakaan kerja. Namun pengawasan tersebut masih manual, sehingga akan memakan waktu lama. Metode yang dapat digunakan untuk pengenalan objek pada citra helmet dan vest keselamatan adalah deeplearning. YOLOv2 merupakan salah satu model deep learning yang dapat digunakan untuk pengenalan objek. Mengingatnya p

APA, Harvard, Vancouver, ISO, and other styles

29

DEVI, RUPA, and AMMENAMMA GARI MANIKANTA. "Advanced Machine Learning Strategies for Chronic Disease Prediction with Effective Data Preprocessing." International Scientific Journal of Engineering and Management 04, no. 03 (2025): 1–7. https://doi.org/10.55041/isjem02526.

Full text

Abstract:

Predicting and detecting these illnesses early can greatly enhance patient outcomes and lessen the cost of healthcare. In order to improve predictive accuracy, this study suggests a machine learning-based approach for predicting chronic diseases that places a strong emphasis on reliable data preprocessing methods. To maximize model performance, the dataset is subjected to categorical encoding, feature scaling, and missing value imputation. Numerous health-related factors, including age, BMI, blood pressure, cholesterol, blood sugar, smoking, exercise frequency, kidney and lung diseases, family

APA, Harvard, Vancouver, ISO, and other styles

30

Jain, Aman, Prof Ritu, and Chirag Saini. "Implementation of Personal Cloud using Cryptography." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 278–81. http://dx.doi.org/10.22214/ijraset.2024.61491.

Full text

Abstract:

Abstract: This Python-based personal cloud application leverages Flask and cryptography to establish a secure file storage system. Employing the Fernet encryption algorithm, the server encrypts uploaded files, ensuring data confidentiality. Users can securely upload, store, and download files, with each file automatically encrypted upon upload and decrypted for download. While this example prioritizes simplicity, a production-ready system should include robust user authentication, access controls, and further security enhancements. The abstract encapsulates the project's essence, highlighting

APA, Harvard, Vancouver, ISO, and other styles

31

Patrick, Kayemba, Abubakhari Sserwadda, Edymond Richard Hirya, Martha Janepher Kisakye, and Rashid Kisejjere. "Cassava Disease Detection Using Machine Learning Techniques." Cross Current International Journal of Agriculture and Veterinary Sciences 7, no. 03 (2025): 64–66. https://doi.org/10.36344/ccijavs.2025.v07i03.002.

Full text

Abstract:

This study examines cassava disease detection using four convolutional neural network (CNN) models: ResNet50, InceptionV3, AlexNet, and VGG16. Cassava, a staple crop in Africa, is threatened by Cassava Mosaic Disease (CMD) and Cassava Brown Streak Disease (CBSD). A dataset from the Lacuna Project, collected in Ugandan farmer fields, was used to train and evaluate these models, yielding accuracies of 90 percent, 88 percent, 85 percent, and 87 percent, respectively. A Flask web application was developed for practical deployment. This work builds on prior SVM and CNN approaches, offering a detail

APA, Harvard, Vancouver, ISO, and other styles

32

RUPADEVI, B. "PLAYER BEHAVIOUR PREDICTION IN GAME PURCHASE USING ML." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem03917.

Full text

Abstract:

Abstract: The gaming industry increasingly relies on predictive analytics to enhance player engagement and optimize in-game purchase revenue. This study develops machine learning models to predict Player Engagement Level (PEL) and Purchase Likelihood (PL) using a dataset of 5,000 player records with 33 features, encompassing gameplay, monetization, social, and demographic attributes. Through exploratory data analysis, feature selection with SelectKBest, and class balancing via SMOTE, the methodology mitigates imbalances and reduces dimensionality to eight key predictors. Four algorithms—Decisi

APA, Harvard, Vancouver, ISO, and other styles

33

Vishnoi, Gaurvi, Rahul Bansal, Arpit Garg, and Atyab Tosif. "Full Page Handwriting Recognition on CUDA enabled Docker." Journal of Artificial Intelligence and Imaging 1, no. 2 (2024): 26–33. http://dx.doi.org/10.48001/joaii.2024.1226-33.

Full text

Abstract:

-Handwritten text recognition is essential for document digitization but often struggles with multiline content. This paper presents an integrated approach using TrOCR, a pre-trained Transformer model, combined with PaddleOCR for enhanced text detection. The integration, optimized with GPU acceleration and multi-threading within a CUDA-enabled Docker environment, addresses the challenges of full-page handwriting recognition. A user-friendly Flask API with a Gradio demo was developed for deployment. Experimental results demonstrate that the system significantly improves the accuracy of multilin

APA, Harvard, Vancouver, ISO, and other styles

34

Kurniawan, Benny, and Radius Tanone. "Implementation of Google Cloud in Business to Business Tanda Tukar Faktur Application." JUITA: Jurnal Informatika 9, no. 2 (2021): 201. http://dx.doi.org/10.30595/juita.v9i2.10321.

Full text

Abstract:

Alfamart is a company engaged in retail. Companies involved in the retail sector are certainly inseparable from buying and selling products, and every transaction that occurs will be detailed in the invoice exchange. The problem that arises is because Alfamart wants to accommodate the electronic invoice exchange process. Therefore, Alfamart built a B2B TTF application that can accommodate the electronic invoice exchange process and help its accounting management. The application is made using the Research and Development method because it can address urgent needs and has a high validation valu

APA, Harvard, Vancouver, ISO, and other styles

35

KUMAR K R, VEERENDRA. "AI-Based Part Identification and Classification Using YOLOv8 and Flask." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem45244.

Full text

Abstract:

The rapid advancement of artificial intelligence (AI) and computer vision has enabled the development of systems capable of identifying and classifying parts of complex items with high accuracy. This paper focuses on building an AI-based system to detect and classify parts of an item, such as components of a machine, car parts, or sections of a product. The system leverages state-of-the-art object detection models, specifically YOLOv8 (You Only Look Once), to achieve real-time and accurate part identification. The paper involves several key steps: data collection and annotation, model selectio

APA, Harvard, Vancouver, ISO, and other styles

36

CHYHIN, Vasyl, Mykhailo PAZYNIUK, Olha TERENDII, and Oleksii MENSHIKOV. "CONTROLLING THE OPERATION OF THE REMOTE DEVICE USING FLASK PYTHON SERVER." Herald of Khmelnytskyi National University. Technical sciences 317, no. 1 (2023): 214–19. http://dx.doi.org/10.31891/2307-5732-2023-317-1-214-219.

Full text

Abstract:

A computer model of controlling an unmanned aerial vehicle (UAV) using remote cloud technologies according to predetermined scenarios from the user’s desktop was studied. For this, an experimental setup was created, which includes an unmanned aerial vehicle of the quadcopter type, a personal computer with the Windows operating system, a Raspberry Pi 3 on-board computer with the Raspbian Linux operating system, a Pi Camera V2 video camera, and a Pixhawk autopilot. Worked out connection sequence between client (web browser user) and server (Raspberry Pi 3 with Flask system) and execution of remo

APA, Harvard, Vancouver, ISO, and other styles

37

Bella Pratiwi. "Penerapan Model Machine Learning dalam Pengembangan Web App “CRACKSAFE” untuk Deteksi Keretakan pada Dinding Bangunan." Inisiatif : Jurnal Dedikasi Pengabdian Masyarakat 3, no. 1 (2024): 59–68. https://doi.org/10.61227/inisiatif.v3i1.148.

Full text

Abstract:

Penelitian ini bertujuan untuk menganalisis penerapan teknologi AI dan Machine Learning dalam aplikasi web CRACKSAFE untuk mendeteksi keretakan pada struktur bangunan. Metode kualitatif digunakan untuk memahami tantangan, kebutuhan, dan potensi solusi dalam deteksi keretakan pada tembok perumahan. Dataset gambar keretakan dan non-keretakan digunakan untuk melatih model deteksi menggunakan YOLOv8, dengan evaluasi model dilakukan menggunakan Mean Average Precision (MAP), F-1 Score, precision, dan recall. Hasilnya menunjukkan kemampuan model dalam mengidentifikasi keretakan dengan baik meskipun m

APA, Harvard, Vancouver, ISO, and other styles

38

Kavitha Soppari, Nuthana Basupally, Harika Toomu, and Pavan Kalyan Bijili. "Offline LLM: Generating human like responses without internet." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 1823–27. https://doi.org/10.30574/wjarr.2025.26.2.1783.

Full text

Abstract:

This study explores the integration of lightweight and offline-capable natural language processing (NLP) tools for extractive and abstractive text summarization in resource-constrained environments. Drawing from foundational work such as TextRank (Mihalcea & Tarau, 2004) and the NLTK toolkit (Bird et al., 2009), the system combines graph-based extractive summarization and frequency-based keyword extraction for efficient offline text analysis. PyMuPDF facilitates accurate PDF text extraction, enabling document conversion into analyzable formats. Abstractive summarization leverages the T5-sm

APA, Harvard, Vancouver, ISO, and other styles

39

Mahalakshmi, S. S. D. K. "Machine Learning Approach for Yield Estimation and Crop Prediction." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47206.

Full text

Abstract:

Abstract - Optimal crop recommendations and yield prediction are essential for improving farm productivity and food security. Conventional approaches to the prediction of crop yields are usually limited by environmental variability. The present work proposes a strong machine learning-based framework aiming to support farmers in the process of choosing the best crops and predicting yield potential more accurately. The suggested system combines three supervised learning techniques—Decision Tree, Random Forest, and XGBoost—to examine critical environmental and soil parameters like nitrogen (N), p

APA, Harvard, Vancouver, ISO, and other styles

40

Vivek Raj Singh, Shwet Ketu. "Advanced Predictive System for Diagnosing Patient Disease through Machine Learning Techniques." Power System Technology 49, no. 1 (2025): 497–508. https://doi.org/10.52783/pst.1562.

Full text

Abstract:

The aim of this research is to develop a web application that predicts multiple diseases, including Diabetes, Breast Cancer, Heart Disease, Alzheimer disease, brain tumor, Covid-19, and Pneumonia, using machine learning and deep learning models. The models were trained on large datasets sourced from Kaggle. The study includes data collection, preprocessing, model selection, and deployment of the trained models. The application uses Python Flask as the web framework, and models such as CNN (for Covid-19, and Pneumonia) are integrated to ensure accurate predictions. This project achieved predict

APA, Harvard, Vancouver, ISO, and other styles

41

Tondarkar, Abhishek A. "AI Driven Vulnerability Analysis Systems." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50022.

Full text

Abstract:

Abstract— With the increasing frequency and sophistication of cyber threats, the need for intelligent and adaptive security solutions has become more critical than ever. Artificial Intelligence (AI) is playing a transformative role in cybersecurity by enhancing the detection of system vulnerabilities, anticipating potential threats, and enabling automated incident response. This research introduces VulneraX, an AI-driven vulnerability analysis system built using the Flask framework. The system is trained on data from the National Vulnerability Database (NVD) covering the years 2020 to 2023. Vu

APA, Harvard, Vancouver, ISO, and other styles

42

Perih, Anastasiia. "Integrating Machine Learning Technologies to Enhance Web Development Efficiency." Universal Library of Engineering Technology 02, no. 01 (2025): 53–60. https://doi.org/10.70315/uloap.ulete.2025.0201010.

Full text

Abstract:

This article explores the application of machine learning technologies in the development of modern web applications, using JavaScript for the frontend, Python for the backend, and Amazon Web Services (AWS) for cloud infrastructure. Given the growing user expectations around personalization and responsive interfaces, the focus is on solutions that extend beyond static architectures. The review encompasses both open-source projects and production-level implementations, enabling the identification of architectural patterns for integrating machine learning into the technology stack. The article e

APA, Harvard, Vancouver, ISO, and other styles

43

Ramesh, Richard Sylvester. "Real-Time Facial Recognition and Behaviour Analysis for Workplace Monitoring." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47852.

Full text

Abstract:

Abstract - Facial recognition systems have become increasingly valuable in workplace environments where real-time identity verification and behavioural monitoring are essential for ensuring safety, security, and operational efficiency. This paper presents a lightweight and cost-effective facial recognition system designed specifically for workplace monitoring, integrating both identity recognition and behaviour analysis using classical computer vision techniques. The system employs Haar Cascade classifiers for real-time face detection, utilizing OpenCV for image processing and Flask as the bac

APA, Harvard, Vancouver, ISO, and other styles

44

Irfanuddin, Muhammad Saifullah, Mukhamad Nurkamid, and Tutik Khotimah. "Klasifikasi Tingkat Kematangan Belimbing Madu Berdasarkan Karakteristik Warna Menggunakan Algoritma K-Nearest Neighbor." Jurnal Dialektika Informatika (Detika) 4, no. 2 (2024): 65–73. http://dx.doi.org/10.24176/detika.v4i2.12804.

Full text

Abstract:

Penelitian ini menggunakan teknologi pengolahan citra digital untuk mengembangkan sistem klasifikasi tingkat kematangan belimbing madu berdasarkan fitur warna menggunakan model warna HSV. Metode K-Nearest Neighbor (K-NN) diterapkan untuk klasifikasi tingkat kematangan buah tersebut, dengan Google Colab sebagai alat utama dalam analisis citra dan pengolahan data. Tujuan penelitian ini adalah mengklasifikasikan tingkat kematangan belimbing madu berdasarkan fitur warna dengan algoritma K-NN, serta merancang sistem yang dapat mengenali dan membedakan tiga tingkat kematangan: mentah, setengah matan

APA, Harvard, Vancouver, ISO, and other styles

45

N, KEERTHI, CHETANA P. SUTHAR, and LEKHANA E. "REAL-TIME ACCENT TRANSLATOR." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40714.

Full text

Abstract:

This paper introduces the "Real-Time Accent Translator," a lightweight and accessible web-based application that bridges the gap between multilingual communication and accent adaptation. Built on Flask, the system integrates Google Translate and Google Text-to-Speech (gTTS) APIs to provide seamless translation and speech synthesis. Users can input text in a source language, specify the target language, and optionally adjust accents for languages such as English. The application translates the text, synthesizes speech with the desired accent, and provides an audio output in real time. The archi

APA, Harvard, Vancouver, ISO, and other styles

46

Mitropoulos, Spyridon, Dimitrios Rimpas, Stylianos Katsoulis, George Hloupis, and Ioannis Christakis. "Integrated Low Cost, LoRa-Based, Real Time Fluid Infusion Flask Monitoring System." Electronics 14, no. 5 (2025): 869. https://doi.org/10.3390/electronics14050869.

Full text

Abstract:

Manual intravenous (IV) monitoring delays, put patients at risk, as the reaction time of nursing staff can be critical to the patient’s health. The widespread use of LoRa networks today is a reality. The deployment of devices and applications based on LoRa networks in healthcare environments, such as hospital facilities, is of great interest and can offer both time savings for medical and nursing staff and improvements in medical care. In this work an integrated low-cost, real-time monitoring system for fluid infusion based on a LoRa network is presented. The measured (monitoring) data are the

APA, Harvard, Vancouver, ISO, and other styles

47

Kumar, Dr C. Srinivasa. "Brain Tumor Detection Using Deep Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50618.

Full text

Abstract:

Abstract— Abstract — Brain tumors are among the most life-threatening and complex conditions, requiring early and accurate detection to ensure effective treatment and improved survival rates. Manual interpretation of MRI scans for diagnosis is a labor-intensive process, demanding significant expertise and carrying the risk of human inaccuracies. This research proposes a deep learning-based framework using a Deep Convolutional Neural Network (DCNN) specifically instantiated with the pretrained ResNet50 model for the automated detection and classification of brain tumors from MRI images. MRI sca

APA, Harvard, Vancouver, ISO, and other styles

48

Singhania, Ruchita, Sana Badagan, Deeksha Reddy, K. Tarun Sai Teja, and Chetan Jetty. "Medibuddy - A Healthcare Chatbot using AI." International Journal of Soft Computing and Engineering 14, no. 3 (2024): 14–19. http://dx.doi.org/10.35940/ijsce.g9902.14030724.

Full text

Abstract:

This paper presents the development of a Flask-based web application designed to predict diseases based on user-reported symptoms and provide relevant health information. Leveraging machine learning techniques, the system utilizes a dataset of diseases and their associated symptoms to generate predictions through cosine similarity and a pre-trained Random Forest model. The application features a user-friendly interface for registration, login, and symptom reporting. Additionally, it integrates the DuckDuckGo search API to fetch detailed information about predicted diseases, enhancing the user

APA, Harvard, Vancouver, ISO, and other styles

49

Punjabi, Jayesh, Neeraj Shilwant, Vinit Ghadge, Shubham Sonawane, and Dr Bhagyashree Tingare. "GitHub Profile Rating and Analysis Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 5518–24. http://dx.doi.org/10.22214/ijraset.2024.62883.

Full text

Abstract:

Abstract: Assessing developer engagement and impact in the changing world of software development is an important task for employers, partners, and the developers themselves. GitHub, the leading code hosting and collaborative development platform, provides rich data for such testing. This article introduces GitHub Profile Analyzer, a new tool that uses artificial intelligence (AI) and data science to analyse and evaluate GitHub profiles. The system uses a gradient boosting regressor model to evaluate profiles based on a variety of metrics, including user activity, data retention, and engagemen

APA, Harvard, Vancouver, ISO, and other styles

50

Dhanwate, Prof P. "Multiple Disease Prediction System Using ML." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 3612–17. http://dx.doi.org/10.22214/ijraset.2024.59642.

Full text

Abstract:

Abstract: The increasing prevalence of diverse diseases presents a challenge to global healthcare systems, underscoring the need for innovative and efficient methods for early detection and preventive measures. This paper explores the application of machine learning algorithms in multiple disease prediction to enhance diagnostic accuracy and enable timely intervention. Leveraging diverse health-related data sources, including medical records and genomic information, comprehensive predictive models are developed. A multi-faceted machine learning approach integrates support vector machines, deci

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!