Paper Accepted at ICECTE 2026

DeepNet Lab is pleased to announce that a paper by our Undergraduate Research Assistant has been accepted at the International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE 2026). The paper, titled "Facial Emotion Recognition with Attention-Driven Deep Learning: A Lightweight Custom Architecture and Ensemble-Based Framework," represents collaborative research by our undergraduate team. The research introduces a lightweight custom architecture for facial emotion recognition using attention-driven deep learning techniques. The ensemble-based framework demonstrates improved performance while maintaining computational efficiency, making it suitable for real-world applications. **Authors:** - Khaled Ahmed (Undergraduate Research Assistant) - Nazmul Islam (Undergraduate Research Assistant) - Tajkia Jannath Chowdhury (Undergraduate Research Assistant) All accepted papers will be published in IEEE Xplore, providing global visibility to our undergraduate researchers' work. "This achievement showcases the talent and dedication of our undergraduate research team," said Md. Jalal Uddin Chowdhury. "Having their work accepted at an international conference and published in IEEE Xplore is a significant milestone in their academic journey." ICECTE is a premier international conference that brings together researchers, practitioners, and experts to share cutting-edge developments in electrical, computer, and telecommunication engineering. This acceptance reflects DeepNet Lab's commitment to nurturing young research talent and providing them with opportunities to contribute to meaningful research at the international level.