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Simegnew Yihunie Alaba

About

Simegnew Yihunie Alaba completed his Ph.D. in Electrical and Computer Engineering at Mississippi State University in May 2024. He has been working as a Perception Engineer. His research focuses on computer vision, deep learning, machine learning, and autonomous driving. He is committed to fostering cross-disciplinary collaborations, leveraging state-of-the-art techniques, and remaining at the forefront of research to drive engineering and artificial intelligence advancements.

Education

Research Areas

  • Computer Vision
  • Deep Learning
  • Machine Learning
  • Perception and Localization for Autonomous Driving/Robotics

Publications

Multimodal Fusion
Deep Learning 3D Object Detection
Deep Learning-Based Image 3D Object Detection for Autonomous Driving

Simegnew Yihunie Alaba, John E. Ball

IEEE Sensors, 2023

Deep Learning LiDAR 3D Object Detection
A Survey on Deep-Learning-Based LiDAR 3D Object Detection for Autonomous Driving

Simegnew Yihunie Alaba, John E. Ball

MDPI Sensing and Imaging, 2022

WCAM
WCAM: Wavelet Convolutional Attention Module

Simegnew Alaba, John E. Ball

IEEE SoutheastCon, April 2024

WCAM
YOLOv8-TF: Transformer-Enhanced YOLOv8 for Underwater Fish Species Recognition with Class Imbalance Handling

Chiranjibi Shah, M M Nabi, Simegnew Yihunie Alaba, et al.

Sensing and Imaging, March 2025

Multimodal Fusion
Emerging Trends in Autonomous Vehicle Perception: Multimodal Fusion for 3D Object Detection

Simegnew Alaba, ALi C Gurbuz, John E. Ball

World Electric Vehicle Journal, January 7, 2024

SmRNet
SmRNet: Scalable Multiresolution Feature Extraction Network

Simegnew Alaba, John E. Ball

IEEE ICECET, November 16-17, 2023

Multi-Sensor Fusion
Multi-sensor fusion 3D object detection for autonomous driving

Simegnew Yihunie Alaba, John E. Ball

Autonomous Systems: Sensors, Processing and Security for Ground, Air, Sea, and Space Vehicles, April 30 – May 4, 2023

Model Performance with Metrics
Optimizing and Gauging Model Performance with Metrics to Integrate with Existing Video Surveys

Jack Prior, Simegnew Yihunie Alaba, et al.

IEEE Ocean Conference & Exposition Biloxi, MS, USA, September 25-28, 2023

Probabilistic Model-based Active Learning
Probabilistic Model-based Active Learning with Attention Mechanism for Fish Species Recognition

M M Nabi, Chiranjibi Shah, Simegnew Yihunie Alaba, et al.

IEEE Ocean Conference & Exposition Biloxi, MS, USA, September 25-28, 2023

Probabilistic Model-based Active Learning
A Zero Shot Detection Based Approach for Fish Species Recognition in Underwater Environments

Chiranjibi Shah, M M Nabi, Simegnew Yihunie Alaba, et al.

IEEE Ocean Conference & Exposition Biloxi, MS, USA, September 25-28, 2023

Multi-Sensor Fusion
Semi-supervised Learning for Fish Species Recognition

Simegnew Yihunie Alaba, John E. Ball

Ocean Sensing and Monitoring XV: Machine Learning/Deep Learning 1, Orlando, FL, USA, April 30 – May 4, 2023

YOLOv5 Model
An Enhanced YOLOv5 Model for Fish Species Recognition

Chiranjibi Shah, Simegnew Yihunie Alaba, et al.

Ocean Sensing and Monitoring XV, April 2023

Class-Aware Fish Species Recognition
Class-Aware Fish Species Recognition Using Deep Learning for an Imbalanced Dataset

Simegnew Yihunie Alaba,M M Nabi, John E. Ball, et al.

MDPI Sensing and Imaging, 2022

Wavelet Convolutional Neural Network
WCNN3D: Wavelet Convolutional Neural Network-Based 3D Object Detection for Autonomous Driving

Simegnew Yihunie Alaba, John E. Ball

MDPI Sensing and Imaging, 2022

Multifish tracking
Multifish tracking for marine biodiversity monitoring

Simegnew Yihunie Alaba, Jack H. Prior, et al.

Ocean Sensing and Monitoring XVI, April 2024

GPS-IMU Sensor Fusion
Active detection
Active detection for fish species recognition in underwater environments

Chiranjibi Shah, M M Nabi, Simegnew Yihunie Alaba, et al.

Ocean Sensing and Monitoring XVI, April 2024

Inconsistency-based active learning
Inconsistency-based active learning with adaptive pseudo-labeling for fish species identification

M M Nabi, Chiranjibi Shah, Simegnew Yihunie Alaba, et al.

Ocean Sensing and Monitoring XVI, April 2024

automated video post-processing
SEAMAPD21
SEAMAPD21: a large-scale reef fish dataset for fine-grained categorization

Océane Boulais, Simegnew Yihunie Alaba, et al.

IEEE CVPR FGVC8: The Eight Workshop on Fine-Grained Visual Categorization, 2021

Blog

A Complete Guide to Point Cloud Processing
A Comprehensive Guide to Attention Mechanisms in CNNs: From Intuition to Implementation
Installing Intel RealSense D435i Camera on Nvidia Jetson Orin NX: Step-by-Step Guide
Arrays vs. Vectors in Modern C++: A Detailed Comparison with Examples

Volunteer Work

  • Science Fair Judge for high school students, Starkville, MS, February 2022 & March 2023.
  • Journal Reviewer for IEEE Access, IEEE Sensors Journal, and IEEE Transactions On Intellignet Transportation Systems.