• DEVELOPING EXPLAINABLE AI-BASED PROTOTYPE FOR DETECTION OF FETAL ABNORMALITIES 

  SISAY, NEGASH MENGISTU (2024-08)

  Obstetrics is a medical specialty focused on pregnancy, childbirth, and postpartum care, ensuring the health of both mother and baby. It involves diagnosing and addressing fetal anomalies during prenatal care. Fetal ...
• SOFTWARE EFFORT ESTIMATION USING OBJECT POINT ANALYSIS 

  SHIMELS, TILAHUN (2023-07)

  Software effort estimation is a critical aspect of software project management that involves predicting the energy required to develop the software project from planning to deployment. Delivering high-quality software that ...
• SOFTWARE TESTING EFFORT ESTIMATION MODEL USING MACHINE LEARNING APPROACHES 

  HALIMA, AYENEW BEHAREA (2024-03)

  Producing high-quality software within budget constraints and on a tight schedule is a crucial aspect of software projects. Much like the challenges faced in software development, software testing processes are prone to ...
• Developing Lake Evaporation Prediction Model Using Deep Learning: The Case of Lake Tana 

  Emebet, Tadesse Fentie (2024-03)

  Lake evaporation rate and evaporation volume prediction is getting attention from the scientific community and government policy makers because of the dramatic global climate change and the key role evaporation plays in ...
• SELECTION OF SOFTWARE DEVELOPMENT LIFE CYCLE MODELS USING MACHINE LEARNING APPROACH 

  DIRES, BITEW ANILEY (2024-07)

  Inappropriate selection of Software Development Life Cycle (SDLC) models can lead to increased development time and costs, heightened overhead, elevated risk exposure, difficulty in managing uncertainty, reduced quality, ...
• SOFTWARE ARCHITECTURAL TACTICS SELECTION BASED ON QUALITY ATTRIBUTE REQUIREMENTS USING MACHINE LEARNING 

  MEKURIAW, KASSIE (2023-12)

  In software development, developers perform different activities so as to meet the needs of the user or get the full functionality of the software system. Among the different activities, requirement gathering and addressing ...
• END TO END SPEECH RECOGNITION FOR AMHARIC LANGUAGE USING DEEP LEARNING 

  Yohannes, Ayana (2023-07)

  Speech recognition, also known as automatic speech recognition (ASR), is a technology that enables software to transcribe spoken language into text. However, traditional ASR methods require multiple separate blocks, ...
• DEVELOP THE HERBS PLANT CLASSIFICATIONMODEL FOR PATIENT CARE USING DEEP LEARNING 

  SURAFEL, AMSALU TADESSE (2023-06)

  This paper focuses on noise removal in the classification and description of herbal plants using the Xception model. The study aims to improve accuracy by addressing challenges related to shadow removal, dust removal, ...
• AMHARIC CAPTION GENERATION FROM HOLY PICTURES USING DEEP LEARNING 

  AGEGNEHU, TESHOME (2023-06)

  The widespread availability of portable cameras and mobile phone cameras has led to a significant increase in the number of captured images. However, effectively describing the information contained in these images remains ...
• Amharic-Khimtagne Bi-directional Machine Translation Using Deep Learning 

  Adane, Kasie Chekole (2023-07)

  r Amharic-Khimtagne and Khimtagne-Amharic translations, respectively. The main limitation of this research is the lack of sufficient datasets to conduct an entire experiment. Therefore, it is necessary to collect ...

• DEVELOPING EXPLAINABLE AI-BASED PROTOTYPE FOR DETECTION OF FETAL ABNORMALITIES 

  SISAY, NEGASH MENGISTU (2024-08)

  Obstetrics is a medical specialty focused on pregnancy, childbirth, and postpartum care, ensuring the health of both mother and baby. It involves diagnosing and addressing fetal anomalies during prenatal care. Fetal ...
• SOFTWARE EFFORT ESTIMATION USING OBJECT POINT ANALYSIS 

  SHIMELS, TILAHUN (2023-07)

  Software effort estimation is a critical aspect of software project management that involves predicting the energy required to develop the software project from planning to deployment. Delivering high-quality software that ...
• SOFTWARE TESTING EFFORT ESTIMATION MODEL USING MACHINE LEARNING APPROACHES 

  HALIMA, AYENEW BEHAREA (2024-03)

  Producing high-quality software within budget constraints and on a tight schedule is a crucial aspect of software projects. Much like the challenges faced in software development, software testing processes are prone to ...
• Developing Lake Evaporation Prediction Model Using Deep Learning: The Case of Lake Tana 

  Emebet, Tadesse Fentie (2024-03)

  Lake evaporation rate and evaporation volume prediction is getting attention from the scientific community and government policy makers because of the dramatic global climate change and the key role evaporation plays in ...
• SELECTION OF SOFTWARE DEVELOPMENT LIFE CYCLE MODELS USING MACHINE LEARNING APPROACH 

  DIRES, BITEW ANILEY (2024-07)

  Inappropriate selection of Software Development Life Cycle (SDLC) models can lead to increased development time and costs, heightened overhead, elevated risk exposure, difficulty in managing uncertainty, reduced quality, ...
• SOFTWARE ARCHITECTURAL TACTICS SELECTION BASED ON QUALITY ATTRIBUTE REQUIREMENTS USING MACHINE LEARNING 

  MEKURIAW, KASSIE (2023-12)

  In software development, developers perform different activities so as to meet the needs of the user or get the full functionality of the software system. Among the different activities, requirement gathering and addressing ...
• END TO END SPEECH RECOGNITION FOR AMHARIC LANGUAGE USING DEEP LEARNING 

  Yohannes, Ayana (2023-07)

  Speech recognition, also known as automatic speech recognition (ASR), is a technology that enables software to transcribe spoken language into text. However, traditional ASR methods require multiple separate blocks, ...
• DEVELOP THE HERBS PLANT CLASSIFICATIONMODEL FOR PATIENT CARE USING DEEP LEARNING 

  SURAFEL, AMSALU TADESSE (2023-06)

  This paper focuses on noise removal in the classification and description of herbal plants using the Xception model. The study aims to improve accuracy by addressing challenges related to shadow removal, dust removal, ...
• AMHARIC CAPTION GENERATION FROM HOLY PICTURES USING DEEP LEARNING 

  AGEGNEHU, TESHOME (2023-06)

  The widespread availability of portable cameras and mobile phone cameras has led to a significant increase in the number of captured images. However, effectively describing the information contained in these images remains ...
• Amharic-Khimtagne Bi-directional Machine Translation Using Deep Learning 

  Adane, Kasie Chekole (2023-07)

  r Amharic-Khimtagne and Khimtagne-Amharic translations, respectively. The main limitation of this research is the lack of sufficient datasets to conduct an entire experiment. Therefore, it is necessary to collect ...
• Multitask Deep Learning Approach for Habesha Fashion Cloth Recognition and Classification 

  Yohannes, Abenet (2023-06)

  Multitask learning is the most popular concept in deep learning, aiming to exploit the correlation among tasks. To achieve this, the learning of different tasks is performed jointly. This research proposes a deep ...
• SOFTWARE RISK PREDICTION AT REQUIREMENT AND DESIGN PHASE : AN ENSEMBLE MACHINE LEARNING APPROACH 

  YIBELTAL, ASSEFA (2023-06)

  Software development is a highly structured process that involves the creation and maintenance of a particular system, ranging from simple applications to complex enterprise software. Despite following a well-defined ...
• SOCIAL MEDIA SENTIMENT ANALYSIS FOR SERVICE CLASSIFICATION 

  TALAKSEW, KASSA YAZEW (2023-07)

  Social media analysis is an essential mechanism for organizations to grasp new knowledge and information from social media data. In social media analysis, sentiment analysis and service classification are ...
• USE CASE IDENTIFICATION FROM THE REQURIMENT TEXTS USING MACHINE LEARNING APPROACH 

  TADILO, GETANEH GELAGAY (2023-06)

  The requirement gathering and design phases play important roles in the software development lifecycle. One of the requirements gathering phases is identifying the use case and actors. A use case is a specification of ...
• CLASSIFICATION AND PRIORITIZATION OF REQUIREMENTS SMELLS USING MACHINE LEARNING ALGORITHMS 

  FEKERTE, BERHANU TADLE (2023-07)

  Software requirements are a description of what the software is expected to do and behave. Specifying requirements in natural language might face difficulties like clarity, inaccuracy, ambiguity, incompleteness, ...
• SOFTWARE MAINTAINABILITY AND RELIABILITY MODEL USING PROCESS METRICS AND MACHINE LEARNING TECHNIQUES. 

  Asnakech, Tilahun (2023-07)

  Software maintainability and reliability are important components in making sure that the software systems can utilize for a long time. Process metrics in conjunction with machine learning approaches used to enhance software ...
• Scamming Detection from social media using Deep Learning Approach 

  Amare, Lakew (2023-02)

  Scamming is the practice of using tricks to obtain money or goods from another person. Scams often involve making false promises of quick riches or easy money or tricking victims into handing over personal or banking ...
• Test Case Generation from Testable Quality Attribute Scenarios using Machine Learning Approach 

  Abebaw, Worku Chekol (2023-06)

  Software testing plays a critical role in ensuring the quality of software systems by verifying the system. To enforce quality, it is essential to identify testable quality attribute scenarios and predict relevant test ...
• ETHIOPIAN ORTHODOX TEWAHIDO CHURCH AQUAQUAM ZEMA CLASSIFICATION MODEL USING DEEP LEARNING 

  BAYE, TADESSE DAGNEW (2023-03-16)

  Research has been done to automatically classify music genres based on their sound for music information retrieval (MIR) systems, music data analysis, and music transcription purposes. When the amount of music data ...
• AUTOMATIC MISPRONUNCIATION DETECTION FOR GE’EZ LANGUAGE USING DEEP LEARNING APPROACH 

  ABRAHAM, DEMLEW (2022-09)

  Ge‘ez is an ancient Semitic language of Ethiopia, which survives as the liturgical language of the Ethiopian Orthodox Tewahedo Church (EOTC) and Eritrean Orthodox Tewahedo Church. Beyond EOTC, ...

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