Hierarchical machine learning for high-fidelity 3D printed biopolymers
A hierarchical machine learning (HML) framework is presented that uses a small dataset to
learn and predict the dominant build parameters necessary to print high-fidelity 3D features …
learn and predict the dominant build parameters necessary to print high-fidelity 3D features …
Optimizing CNN hyperparameters for blastocyst quality assessment in small datasets
Morphological assessment of blastocyst quality is one of the most significant challenges in
the IVF process because the current assessment is based on evaluation by an embryologist; …
the IVF process because the current assessment is based on evaluation by an embryologist; …
A mixed reality system combining augmented reality, 3D bio-printed physical environments and inertial measurement unit sensors for task planning
Successful surgical operations are characterized by preplanning routines to be executed
during actual surgical operations. To achieve this, surgeons rely on the experience acquired …
during actual surgical operations. To achieve this, surgeons rely on the experience acquired …
Automatic Inspection of Seal Integrity in Sterile Barrier Packaging: A Deep Learning Approach
JZ Diaz, MA Farooq, P Corcoran - IEEE Access, 2024 - ieeexplore.ieee.org
The digitalisation of visual tasks through imaging techniques and Computer Vision has the
potential to disrupt the manner in which Advanced Manufacturing processes are deployed …
potential to disrupt the manner in which Advanced Manufacturing processes are deployed …
Toward Non-Invasive Diagnosis of Bankart Lesions with Deep Learning
S Sethi, S Reddy, M Sakarvadia, J Serotte… - arXiv preprint arXiv …, 2024 - arxiv.org
Bankart lesions, or anterior-inferior glenoid labral tears, are diagnostically challenging on
standard MRIs due to their subtle imaging features-often necessitating invasive MRI …
standard MRIs due to their subtle imaging features-often necessitating invasive MRI …