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Found 14 papers, 1 papers with code
Enhancing Bangla Fake News Detection Using Bidirectional Gated Recurrent Units and Deep Learning Techniques
We carry out comprehensive trials to show the effectiveness of these models in identifying bogus news in Bangla, with the Bidirectional GRU model having a stunning accuracy of 99. 16%.
Comparative study of Deep Learning Models for Binary Classification on Combined Pulmonary Chest X-ray Dataset
We compared the binary classification performance of eight prominent deep learning models: DenseNet 121, DenseNet 169, DenseNet 201, EffecientNet b0, EffecientNet lite4, GoogleNet, MobileNet, and ResNet18 for their binary classification performance on combined Pulmonary Chest Xrays dataset.
IoMT-Blockchain based Secured Remote Patient Monitoring Framework for Neuro-Stimulation Device
Data from the Internet of Things is gathered, analyzed, and stored in a single location.
Unleashing the Power of Extra-Tree Feature Selection and Random Forest Classifier for Improved Survival Prediction in Heart Failure Patients
In this study, we explore the potential of utilizing data pre-processing techniques and the Extra-Tree (ET) feature selection method in conjunction with the Random Forest (RF) classifier to improve survival prediction in heart failure patients.
Comparative Analysis of Epileptic Seizure Prediction: Exploring Diverse Pre-Processing Techniques and Machine Learning Models
In this research, we present a comprehensive comparative analysis of five machine learning models - Random Forest (RF), Decision Tree (DT), Extra Trees (ET), Logistic Regression (LR), and Gradient Boosting (GB) - for the prediction of epileptic seizures using EEG data.
JutePestDetect: An Intelligent Approach for Jute Pest Identification Using Fine-Tuned Transfer Learning
In certain Asian countries, Jute is one of the primary sources of income and Gross Domestic Product (GDP) for the agricultural sector.
PotatoPestNet: A CTInceptionV3-RS-Based Neural Network for Accurate Identification of Potato Pests
Potatoes are the third-largest food crop globally, but their production frequently encounters difficulties because of aggressive pest infestations.
A Comparative Analysis of CNN-Based Pretrained Models for the Detection and Prediction of Monkeypox
As a result, there is an urgent need for a novel technique to combat and anticipate the disease in the early phases of individual virus infection.
The Role of Digital Agriculture in Transforming Rural Areas into Smart Villages
From the perspective of any nation, rural areas generally present a comparable set of problems, such as a lack of proper health care, education, living conditions, wages, and market opportunities.
Efficient approach of using CNN based pretrained model in Bangla handwritten digit recognition
Moreover, fewer studies have been done on Bangla handwritten digit recognition (BHwDR).
CNN based Intelligent Streetlight Management Using Smart CCTV Camera and Semantic Segmentation
One of the most neglected sources of energy loss is streetlights which generate too much light in areas where it is not required.
A novel approach to increase scalability while training machine learning algorithms using Bfloat 16 in credit card fraud detection
With this increase, fraud in credit cards also has a huge problem and loss to the banks and customers alike.
AI Based Chatbot: An Approach of Utilizing On Customer Service Assistance
This system will work based on the text as a conversational agent that can interact with humans by natural language.
Efficiency Comparison of AI classification algorithms for Image Detection and Recognition in Real-time
Face detection and identification is the most difficult and often used task in Artificial Intelligence systems.
