2 citations · 6 across the 5 of their papers we have counts for
6 papers
Toward AI-Driven Phytoplankton Event Detection from Image Classification: Temporal Aggregation Under Domain Shift
Ali Rohan, Hassan Shayan, Han-Gue Jo +1
Imaging FlowCytobot (IFCB) systems generate large volumes of phytoplankton imagery that exceed the capacity of manual expert analysis. Although machine-learning approaches achieve…
A Systematic Literature Review on Deep Learning-based Depth Estimation in Computer Vision
Ali Rohan, Md Junayed Hasan, Andrei Petrovski
Depth estimation (DE) provides spatial information about a scene and enables tasks such as 3D reconstruction, object detection, and scene understanding. Recently, there has been an…
Exploring the Feasibility of Affordable Sonar Technology: Object Detection in Underwater Environments Using the Ping 360
Md Junayed Hasan, Somasundar Kannan, Ali Rohan +1
This study explores the potential of the Ping 360 sonar device, primarily used for navigation, in detecting complex underwater obstacles. The key motivation behind this research is…
Application of deep learning for livestock behaviour recognition: A systematic literature review
Ali Rohan, Muhammad Saad Rafaq, Md. Junayed Hasan +3
Livestock health and welfare monitoring has traditionally been a labor-intensive task performed manually. Recent advances have led to the adoption of AI and computer vision techniq…
Deep Scattering Spectrum germaneness to Fault Detection and Diagnosis for Component-level Prognostics and Health Management (PHM)
Ali Rohan
In fault detection and diagnosis of prognostics and health management (PHM) systems, most of the methodologies utilize machine learning (ML) or deep learning (DL) through which eit…
Holistic Fault Detection and Diagnosis System in Imbalanced, Scarce, Multi-Domain (ISMD) Data Setting for Component-Level Prognostics and Health Management (PHM)
Ali Rohan
In the current Industrial 4.0 revolution, Prognostics and Health Management (PHM) is an emerging field of research. The difficulty of obtaining data from electromechanical systems…