Search Results
Segment Anything
We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation.
Ranked #2 on
Zero-Shot Instance Segmentation
on LVIS v1.0 val
Trackastra: Transformer-based cell tracking for live-cell microscopy
Importantly, unlike existing transformer-based MOT pipelines, our learning architecture also accounts for dividing objects such as cells and allows for accurate tracking even with simple greedy linking, thus making strides towards removing the requirement for a complex linking step.
Multi-Robot On-site Shared Analytics Information and Computing
In this paper we introduce a communication-aware, computation task scheduling problem for multi-robot systems and propose an integer linear program (ILP) that optimizes the allocation of computational tasks across a network of heterogeneous robots, accounting for the networked robots' computational capabilities and for available (and possibly time-varying) communication links.
Robotics Multiagent Systems
Graphsurge: Graph Analytics on View Collections Using Differential Computation
Users program Graphsurge through a declarative graph view definition language (GVDL) to create views over input graphs and a Differential Dataflow-based programming API to write analytics computations.
Databases
Analytical computation of the epidemic threshold on temporal networks
The time variation of contacts in a networked system may fundamentally alter the properties of spreading processes and affect the condition for large-scale propagation, as encoded in the epidemic threshold.
Physics and Society Populations and Evolution
PixelsDB: Serverless and NL-Aided Data Analytics with Flexible Service Levels and Prices
The queries are then executed by a serverless query engine that offers varying prices for different performance service levels (SLAs).
Serverless Query Processing with Flexible Performance SLAs and Prices
In this paper, we first define the problem of flexible performance SLAs and prices in serverless query processing and discuss its significance.
Databases
Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
Thus, weakly-supervised semantic segmentation techniques are proposed to utilize weak supervision that is cheaper and quicker to acquire.
Hierarchical Graph Representations in Digital Pathology
We propose a novel multi-level hierarchical entity-graph representation of tissue specimens to model hierarchical compositions that encode histological entities as well as their intra- and inter-entity level interactions.
HistoCartography: A Toolkit for Graph Analytics in Digital Pathology
Advances in entity-graph based analysis of histopathology images have brought in a new paradigm to describe tissue composition, and learn the tissue structure-to-function relationship.
