Information System

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Information System [17]

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Red Onion Seed Quality Classification Using Transfer Learning Approaches

WALLE YIRDAWU, TAREKEGN (2024-02-07)

Onion (Allium cepa L.) is a very important vegetable grown all over the world and consumed in various forms. Onion is widely used as a condiment to enhance the flavor of food. Red onion seed (A. fistulosum) is grown ...
Multi-label Chronic Non-Communicable Diseases Prediction Using Machine Learning

Yenehun, Eleni (2024-02-07)

Chronic non-communicable diseases are becoming more prevalent every day, especially in developing countries like Ethiopia. These disorders must be treated as soon as possible. Machine learning-based models can be used ...
Knowledge Base System for Managing, Diagnosing and Treatment of Malnourished Child

Assefa, Gebrehiwot (2024-02-07)

Anthropometry: The study and technique of human body measurement. It is used to measure and monitor nutritional status in an individual or population group. Body measurements include: age, sex, weight, height, oedema ...
AMHARIC-GE’EZ CROSS LANGUAGE INFORMATION RETRIEVAL USING NEURAL MACHINE TRANSLATION

GASHAHUN, WERKAFERAHU (2024-02-07)

Amharic is the working language of the Federal Democratic Republic of Ethiopia (FDRE) and used by the majority of Ethiopians both as mother tongue. Ge'ez on the other hand is the ancient language that was used in Ethiopia. ...
OCCLUSION AWARE FACE MASK DETECTION USING DEEP LEARNING TECHNIQUE

AYECHILUHEM YALEW, TESHOME (2024-02-07)

Cororna virus(Covid-19), occlusion, face mask, InceptionV3, MobileNetV2, DenseNet121, World Health Organization(WHO), Deep learning, Center of Diseases control(CDC), Computer vision.
A Framework for Green and Optimal Usage of Computing Device in Financial Institution of Ethiopia: The Case of Banks

Tesfie, Temesgen (2024-02-07)

This research offers recommendationsthatwill assist the Ethiopian government, stakeholders such as ISPs, as well asowners/managersofbanks, in resolving the problems confronting banks in Ethiopia
Multimodal Amharic Hate Speech Detection Using Deep Learning

Gebremedin, Abreham (24-02-23)

Amharic language, Hate speech, Social media, Multimodal Learning, deep learning, Word2vec, MFCC, LSTM, BILSTM, GRU, BIGRU
Multimodal Amharic Hate Speech Detection Using Deep Learning

Gebremedin, Abreham (2024-12-26)

- Amharic language, Hate speech, Social media, Multimodal Learning, deep learning, Word2vec, MFCC, LSTM, BILSTM, GRU, BIGRU.
Feature Fusion For Amharic Fake News Detection on Social Media Using Machine Learning Technique

Hailu, Menbere (2024-12-30)

Amharic language , Fake news, Social media, Content-based feature, Social-context feature, N-gram,Word2vec, Logistic Regression, Random Forest, Support vector machine.
Predicting the Level of Anemia among Ethiopian Pregnant Women using Homogeneous Ensemble Machine Learning Algorithm and Deploy on Cloud-based Framework

Endalamaw, Belayneh (2024-12-30)

Anemia, Homogeneous Ensemble Machine learning, Flask, Heroku, Class Decomposition
Multimodal Amharic Hate Speech Detection Using Deep Learning

Gebremedin, Abreham (2024-12-30)

Amharic language, Hate speech, Social media, Multimodal Learning, deep learning, Word2vec, MFCC, LSTM, BILSTM, GRU, BIGRU
Predicting Childbirth Modes among Ethiopian Women Using Ensemble Machine Learning Algorithm and Flask Framework

MOGES, MULU (2024-12-30)

childbirth mode, ensemble machine learning, predictive model, pregnant women.
AMHARIC SPEECH TO ETHIOPIAN SIGN LANGUAGE TRANSLATION DEEP LEARNING APPROACH

ABATE, HABTAMU (2024-12-30)

Amharic speech recognition, ESL, Rule-based Machine translation
ENHANCE RECOGNITION OF EOTC SAINT ICONS USING ENSEMBLE OF DEEP LEARNING ALGORITHIM

Assefa, Tiruwork (2024-12-30)

the proposed ensemble model which is EEOTCSIRNET is 99.5% and a total of 3 misclassified images. So the proposed model performance having a promising result and it will have significant when deploy in mobile application ...
Classifying Green Area Coverage of Ethiopia Using Deep Convolutional Neural Network

BAZEZEW GETAHUN, WOYNSHET (2024-12-30)

The researcher finally recommended other researchers to use more than three multispectral images provided by satellite rather than RGB bands and may extend this work to include prediction of green area change
Classifying Severity Level of Psychiatric Symptoms on Twitter Data

Aragaw, Meron (2024-12-30)

psychiatric symptoms, Social media, N-gram, Word2vec, Polarity, Subjectivity Logistic Regression, Random Forest, Support vector machine, Naïve Bayes
Amharic Language Hate Speech Detection on Social Media

Kassa Wondie, Beyene (2024-12-30)

Amharic language, hate speech detection, social media, deep learning

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