A major bottleneck in high-throughput protein crystallography is producing protein-structure models from an electrondensity map. In previous work, we developed Acmi, a probabilist...
This paper presents a method to quantitatively evaluate
information contributions of individual bottom-up and topdown
computing processes in object recognition. Our objective
is...
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
This paper proposes a new registration algorithm, Covariance Driven Correspondences (CDC), that depends fundamentally on the estimation of uncertainty in point correspondences. Th...
We present a collaborative, self-configuring high availability (HA) approach for stream processing that enables low-latency failure recovery while incurring small run-time overhea...