1 citations · 1 across the 7 of their papers we have counts for
7 papers
Standardizing Medical Images at Scale for AI
Callen MacPhee, Yiming Zhou, Koichiro Kishima +1
Deep learning has achieved remarkable success in medical image analysis, yet its performance remains highly sensitive to the heterogeneity of clinical data. Differences in imaging…
Provably effective detection of effective data poisoning attacks
Jonathan Gallagher, Yasaman Esfandiari, Callen MacPhee +1
This paper establishes a mathematically precise definition of dataset poisoning attack and proves that the very act of effectively poisoning a dataset ensures that the attack can b…
Physical Data Embedding for Memory Efficient AI
Callen MacPhee, Yiming Zhou, Bahram Jalali
Deep neural networks (DNNs) have achieved exceptional performance across various fields by learning complex, nonlinear mappings from large-scale datasets. However, they face challe…
Time Stretch with Continuous-Wave Lasers
Tingyi Zhou, Yuta Goto, Takeshi Makino +6
A single-shot measurement technique for ultrafast phenomena with high throughput enables the capture of rare events within a short time scale, facilitating the exploration of rare…
PhyCV: The First Physics-inspired Computer Vision Library
Yiming Zhou, Callen MacPhee, Madhuri Suthar +1
PhyCV is the first computer vision library which utilizes algorithms directly derived from the equations of physics governing physical phenomena. The algorithms appearing in the cu…
VEViD: Vision Enhancement via Virtual diffraction and coherent Detection
Callen MacPhee, Bahram Jalali
The history of computing started with analog computers consisting of physical devices performing specialized functions such as predicting the trajectory of cannon balls. In modern…
Phase-Stretch Adaptive Gradient-Field Extractor (PAGE)
Callen MacPhee, Madhuri Suthar, Bahram Jalali
Phase-Stretch Adaptive Gradient-Field Extractor (PAGE) is an edge detection algorithm that is inspired by physics of electromagnetic diffraction and dispersion. A computational ima…