Students of the BIT program presented a qualitative project titled “Fungi AI.” This intelligent system utilizes Deep Learning and Cloud Integration to discover and classify fungi into five distinct categories via a mobile application. The team included: Hudhaifa Sadiq, Ahmed Essam, Yassin Abdulaziz, Khalil Mohammed, and Suhail Hussein. This project exemplifies the university’s vision of leading digital transformation through practical AI solutions for medical and agricultural challenges.
Fungi AI: Mushroom Detection with Deep Learning
No Images Found!
Combating Deepfake Voice: A Research Project at IUTT Develops a Smart System to Detect Fake Voices with 94% Accuracy
25/04/2026
A research project at IUTT successfully detects deepfake voices with 94% accuracy, employing advanced techniques to combat digital fraud in real-world conditions.
Adaptive MedFusionNet: A Qualitative Research Project at IUTT for Advanced Dermatological Diagnosis using AI
25/04/2026
The “MedFusionNet” project at IUTT utilizes hybrid AI techniques to achieve 94.58% accuracy in dermatological diagnosis and medical decision support.
IUTT Multimedia Students Showcase Creativity in Art and Design Principles Course Projects
25/04/2026
IUTT Multimedia students showcase distinguished projects in Art and Design principles, merging Yemeni identity with modern techniques in the presence of university leadership.