Najoua Essoukri Ben Amara

About

Dr. Najoua Essoukri Ben Amara is a leading researcher at the forefront of computer vision and intelligent surveillance systems. Her work primarily focuses on thermal imaging enhancement, human pose estimation (HPE), and automatic license plate recognition (ALPR), with a strong emphasis on deploying these technologies in real-world, resource-constrained environments. A major contribution is her pioneering use of Generative Adversarial Networks (GANs) to enhance low-contrast thermal images for pedestrian detection, a critical advancement for night-vision and robotics (16 citations). She has also developed robust deep-learning frameworks for full-body HPE from standard RGB video (15 citations), pushing the boundaries of activity recognition. Dr. Ben Amara is particularly recognized for her work on ALPR systems, creating the first publicly available Tunisian license plate dataset (PGTLP) and engineering a dual-stage, real-time recognition system optimized for mobile security robots. Her research, which has garnered over 50 citations, consistently bridges the gap between high-performance deep learning and practical, deployable solutions for surveillance and security.

Research Focus

Key Achievements

Top Papers

1. 1
   Thermal Image Enhancement using Generative Adversarial Network for Pedestrian Detection

   16 citations · 2021
2. 2
   Deep Full-Body HPE for Activity Recognition from RGB Frames Only

   15 citations · 2021
3. 3
   A dual-stage system for real-time license plate detection and recognition on mobile security robots

   8 citations · 2025
4. 4
   Feature distribution alignments for object detection in the thermal domain

   7 citations · 2022
5. 5
   PGTLP: A Dataset for Tunisian License Plate Detection and Recognition

   6 citations · 2021
6. 6
   End-to-End License Plate Recognition System with Optimized Inference on Mobile Security Robots

   2 citations · 2024

Key Collaborators

Contact & Links