Contents
Transfer Learning Based Neural Machine Translation of English-Khasi on Low-Resource Settings
Machine translation for low-resource language can be improved using various techniques. One such technique is the application of knowledge learned by training a model with high-resource language pair to another model with a low-resource language ...
Integration Of Renewable Energy Sources With Power Management Strategy For Effective Bidirectional Vehicle To Grid Power Transfer
The high proportion of Electric vehicles (EV) escalates the demand for rapid charging stations, putting a strain on the present grid infrastructure. Installing charging stations can perform certain jobs, lowering grid effect and assisting the ...
Classification of Breast Thermal Images into Healthy/Cancer Group Using Pre-Trained Deep Learning Schemes
- Seifedine Kadry,
- Rubén González Crespo,
- Enrique Herrera-Viedma,
- Sujatha Krishnamoorthy,
- Venkatesan Rajinikanth
In the women's community, Breast Cancer (BC) is a severe disease. The World Health Organization reported in 2020 that 2.26 million deaths occur due to BC. BC is curable if detected early. Since thermal imaging is non-invasive and supports disease ...
Offline HWR Accuracy Enhancement with Image Enhancement and Deep Learning Techniques
Handwriting recognition (HWR) is the ability of a machine to recognize handwritten text present in images, scanned or photographed. While much of the work reported in this field deals with scanned images, recognizing handwritten content from ...
Sentiment Analysis using Bidirectional LSTM Network
Sentiment analysis is a cognitive tool to extract the emotional tone of a piece of text. It is an area of research that is actively pursued in Natural Language Processing. Social media, forums and blogs, among other places, have seen a massive ...
Detection of Network Attacks using Machine Learning and Deep Learning Models
- K.A. Dhanya,
- Sulakshan Vajipayajula,
- Kartik Srinivasan,
- Anjali Tibrewal,
- T. Senthil Kumar,
- T. Gireesh Kumar
Anomaly-based network intrusion detection systems are highly significant in detecting network attacks. Robust machine learning and deep learning models for identifying network intrusion and attack types are proposed in this paper. Proposed models ...
A Hybrid Classifier-based Ontology driven image Tag Recommendation framework for social image tagging
With the burgeoning of social network sites, social image tagging, where images are annotated with tags, is gaining traction. But, in the domain of social media, this task becomes complex as images are associated with plenitude of object ...
An Attention-based Pneumothorax Classification using Modified Xception Model
Chest radiographs, among other medical imaging, are the most significant and effective diagnostic tools for detecting lung disorders. Numerous research is being done to develop reliable and automatic diagnostic systems for detecting diseases using ...
DynaTrack: Machine Learning Aided Variable Speed Limit System
In the past decade or so, we have seen traffic congestion become a ginormous issue in the major cities of the world, the main reasons for the above being exponential growth in vehicle purchases, constant unplanned maintenance of the road networks, ...
Sarcasm Detection Using Bidirectional Encoder Representations from Transformers and Graph Convolutional Networks
The Internet has become a crucial space for customer feedback and the budding of various ideologies across different cultures. But some people provide their opinions whose sole meaning is different from what their figurative meanings imply. This ...
A Factor Based Multiple Imputation Approach to Handle Class Imbalance
Class imbalance and incompleteness are the two most serious problems faced in data science and machine learning when working on real-life datasets. Both of these cases have severe implications on the ability of classification algorithms to make ...
Smart Facial Emotion Recognition With Gender and Age Factor Estimation
Human-Computer Interaction (HCI) in an intelligent way, which aims at creating scalable and flexible solutions. Big tech firms and businesses believe in the success of HCI as it allows them to profit from on-demand technology and infrastructure ...
A hybrid Data-Driven framework for Spam detection in Online Social Network
Twitter is one of the most prominent online social networks(OSN) used by celebrities, politicians, ordinary people, and organizations to enhance their popularity and brand value. The popularity of Twitter makes it a prime target for spammers to ...
Quality Assessment Model for Handwritten Photo Document Images
The photo document image's quality determines whether it has the potential to be used for information extraction. Document Image Quality Assessment (DIQA) is a difficult task since it is complicated to train a system to have a complete human-like ...
Food Image Classification and Data Extraction Using Convolutional Neural Network and Web Crawlers
Food image recognition is one among the various propitious applications in the area of computer vision. An application with the ability to identify all kinds of food images along with its nutritious value will help people in maintaining a balanced ...
Object Detection on Scene Images: A Novel Approach
Convolutional Neural Networks (CNN) have played an important contribution to the significant development of Computer Vision. An important aspect can be the recognition of objects as it can be an essential part of Computer Vision. CNN's provides a ...
Enhancement in Skin Cancer Detection using Image Super Resolution and Convolutional Neural Network
Skin cancer has been one of the major worldwide public health issue with more than 1 million cases every year. Skin cancer is classified into three categories: Basal Cell Carcinoma, Melanoma and Squamous Cell Carcinoma [1]. Melanoma is the most ...
Machine Learning based Approximate Query Processing for Women Health Analytics
Good health and well being is one of the most essential targets of the Sustainable Development Goals (SDGs). This paper primarily focuses on Preventive and Diagnostic care of Women Health because even today, women are disadvantaged by ...
Identifying Colorectal Tumor For Single Cell RNA Sequence Using Rectified Linear Unit With Stochastic Gradient Descent
To detect cell clusters in whole human colorectal tumor cells, mechanisms based on single-cell RNA sequencing have been reported. To address such issues, a deep learning technique for single-cell analysis was recently developed, with promising ...
Ensemble Machine Learning Paradigms in Software Defect Prediction
Predicting faults in software aims to detect defects before the testing phase, allowing for better resource allocation and high-quality software development, which is a requisite for any organization. Machine learning techniques aid in the ...
Data Mining Based Techniques for Covid-19 Predictions
COVID-19 is a pandemic that has resulted in numerous fatalities and infections in recent years, with a rising tendency in both the number of infections and deaths and the pace of recovery. Accurate forecasting models are important for making ...
Text Sentiment Analysis based on Multichannel Convolutional Neural Networks and Syntactic Structure
Over the last few years, the recognition of social media has grown exponentially, and emotional evaluation in critiques, feedback and evaluations from social media has become extra effective inside the studies field. excessive satisfactory, ...
Acoustic Based Emergency Vehicle Detection Using Ensemble of deep Learning Models
The temporal and spectral structure is possessed in the time-frequency domain by sound events. Analyzing and classifying acoustic environment using sound recording is an emerging research area. Convolutional layers can quickly extract high-level ...
Energy efficient machine learning based SMART-A-BLE implemented Wireless Battery Management System for both Hybrid Electric Vehicles and Battery Electric Vehicles
Electric vehicles have a larger battery pack with more than 100's cells connected in series or parallel combinations to form many battery modules. A Battery Management system (BMS) continuously monitors Current, Voltage, and Temperature data to ...
Early detection of Parkinson's disease using machine learning
Parkinson's disease (PD) is a neurodegenerative disorder affecting 60% of people over the age of 50 years. Patients with Parkinson's (PWP) face mobility challenges and speech difficulties, making physical visits for treatment and monitoring a ...
AIRO: Development of an Intelligent IoT-based Air Quality Monitoring Solution for Urban Areas
Air pollution is the contamination of the atmosphere by any biological, physical, or chemical means. Bengaluru, the Silicon Valley of India, has air pollution levels that exceed WHO standards. Its air has high PM10, PM2.5, SO2, NO2, and CO2 levels,...
A Scheme for Effective Skin Disease Detection using Optimized Region Growing Segmentation and Autoencoder based Classification
Detecting skin disorders just through visual inspection is difficult due to the complicated and overlapping nature of sick lesions, background skin textures, skin hair, low illumination, etc. Computer Vision and Machine Learning are playing a ...
Comparison of Affine and DCGAN-based Data Augmentation Techniques for Chest X-Ray Classification
Data augmentation, also called implicit regularization, is one of the popular strategies to improve the generalization capability of deep neural networks. It is crucial in situations where there is a scarcity of high-quality ground-truth data. ...
Leaf Disease Detection and Classification
The notion of smart farming is gaining traction in the agricultural industry these days, and it makes use of sensors and a variety of machine learning based technologies. According to recent surveys, 56 percent of the agricultural industry is ...