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Found 14 papers, 7 papers with code
3D Reconstruction in Noisy Agricultural Environments: A Bayesian Optimization Perspective for View Planning
3D reconstruction is a fundamental task in robotics that gained attention due to its major impact in a wide variety of practical settings, including agriculture, underwater, and urban environments.
The KiTS21 Challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase CT
Overall KiTS21 facilitated a significant advancement in the state of the art in kidney tumor segmentation, and provides useful insights that are applicable to the field of semantic segmentation as a whole.
Pre-Clustering Point Clouds of Crop Fields Using Scalable Methods
In order to apply the recent successes of machine learning and automated plant phenotyping on a large scale using agricultural robotics, efficient and general algorithms must be designed to intelligently split crop fields into small, yet actionable, portions that can then be processed by more complex algorithms.
Learning Log-Determinant Divergences for Positive Definite Matrices
There exist several similarity measures for comparing SPD matrices with documented benefits.
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge
The 2019 Kidney and Kidney Tumor Segmentation challenge (KiTS19) was a competition held in conjunction with the 2019 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) which sought to address these issues and stimulate progress on this automatic segmentation problem.
The Role of Publicly Available Data in MICCAI Papers from 2014 to 2018
Widely-used public benchmarks are of huge importance to computer vision and machine learning research, especially with the computational resources required to reproduce state of the art results quickly becoming untenable.
Estimating Pedestrian Moving State Based on Single 2D Body Pose
The Crossing or Not-Crossing (C/NC) problem is important to autonomous vehicles (AVs) for safe vehicle/pedestrian interactions.
The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes
The morphometry of a kidney tumor revealed by contrast-enhanced Computed Tomography (CT) imaging is an important factor in clinical decision making surrounding the lesion's diagnosis and treatment.
Convolutional Neural Networks for Aircraft Noise Monitoring
Air travel is one of the fastest growing modes of transportation, however, the effects of aircraft noise on populations surrounding airports is hindering its growth.
Imperfect Segmentation Labels: How Much Do They Matter?
Labeled datasets for semantic segmentation are imperfect, especially in medical imaging where borders are often subtle or ill-defined.
Learning Discriminative ab-Divergences for Positive Definite Matrices
Symmetric positive definite (SPD) matrices are useful for capturing second-order statistics of visual data.
Learning Discriminative Alpha-Beta-divergence for Positive Definite Matrices (Extended Version)
Symmetric positive definite (SPD) matrices are useful for capturing second-order statistics of visual data.
Autonomous 3D Reconstruction Using a MAV
An approach is proposed for high resolution 3D reconstruction of an object using a Micro Air Vehicle (MAV).
Video Human Segmentation using Fuzzy Object Models and its Application to Body Pose Estimation of Toddlers for Behavior Studies
Video object segmentation is a challenging problem due to the presence of deformable, connected, and articulated objects, intra- and inter-object occlusions, object motion, and poor lighting.
