Results 51 to 60 of about 103,598 (304)

Simple Unsupervised Multi-Object Tracking

CoRR, 2020
Multi-object tracking has seen a lot of progress recently, albeit with substantial annotation costs for developing better and larger labeled datasets. In this work, we remove the need for annotated datasets by proposing an unsupervised re-identification network, thus sidestepping the labeling costs entirely, required for training.
Shyamgopal Karthik, Ameya Prabhu, Vineet Gandhi   +2 more
openaire   +2 more sources

Learn-select-track: An approach to multi-object tracking [PDF]

Signal Processing: Image Communication, 2019
Abstract Object tracking algorithms rely on user input to learn the object of interest. In multi-object tracking, this can be a challenge when the user has to provide a lot of locations to track. This paper presents a new approach that reduces the need for user input in multi-tracking. The approach uses density based clustering to analyse the colours
Onalenna J. Makhura, John C. Woods
openaire   +2 more sources

Correlation‐guided multi‐object tracking with correlation feature transfer

IET Computer Vision, 2019
Here, the authors propose a correlation‐guided Monte Carlo Markov chain (MCMC) solver to promote the efficiency for tracking multiple objects under recursive Bayesian filtering framework.
Jiatong Li, Yanjie Zhao, Zhiguo Jiang
doaj   +1 more source

Longitudinal circulating tumor DNA profiling in patients with advanced endometrial cancer using an off‐the‐shelf targeted NGS panel

Molecular Oncology, EarlyView.
Intratumour heterogeneity complicates precision management of advanced endometrial cancer. Circulating tumor DNA (ctDNA) offers a minimally invasive strategy to capture tumor evolution and therapeutic resistance. Here, we compare tumor‐agnostic NGS with tumor‐informed ddPCR, outlining their relative sensitivity, concordance, and clinical implications ...
Carlos Casas‐Arozamena, Karin Teien Lande, Eva Diaz, Ana Vilar, Juan Cueva, Efigenia Arias, Victoria Sampayo, Alicia Abalo, Nerea González, Eva Colás, Antonio Gil‐Moreno, Miguel Abal, Gema Moreno‐Bueno, Therese Sørlie, Kristina Lindemann, Laura Muinelo‐Romay   +15 more
wiley   +1 more source

Parallel algorithm implementation for multi‐object tracking and surveillance

IET Computer Vision, 2016
A recently developed sparse representation algorithm, has been proved to be useful for multi‐object tracking and this study is a proposal for developing its parallelisation. An online dictionary learning is used for object recognition.
Mohamed Elbahri, Nasreddine Taleb, Kidiyo Kpalma, Joseph Ronsin   +3 more
doaj   +1 more source

Deep Network Flow for Multi-object Tracking [PDF]

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Accepted to CVPR ...
Samuel Schulter, Paul Vernaza, Wongun Choi, Manmohan Chandraker   +3 more
openaire   +2 more sources

Circulating tumor cell viability during and after radiotherapy mirrors treatment response in cancer patients

Molecular Oncology, EarlyView.
Radiotherapy (RT) response depends on the DNA repair capacity of tumor and host cells. We show that circulating tumor cell (CTC) counts and apoptosis rates before and after RT predict treatment response and outcome, which can be accessed via easily accessible liquid biopsy approaches. Created in BioRender. Wikman, H.
Yvonne Goy, Jana Löptien, Cornelia Coith, Afroditi Nanou, Katharina Hintelmann, Pinnschmidt Hans, Cordula Petersen, Klaus Pantel, Sabine Riethdorf, Kerstin Borgmann, Harriet Wikman   +10 more
wiley   +1 more source

Real-time multiple object tracking using virtual shells [PDF]

, 2012
This paper presents a new multiple object tracking framework where arbitrarily shaped complex objects having severe occlusions are successfully tracked in real-time using stationary cameras.
Erdoğan, Hakan, Kekeç, İbrahim Taygun, Ünel, Mustafa   +2 more
core  

Patient therapy outcome modeling in cancer organoids is improved by cancer‐associated fibroblasts and organoid assembly convolution

Molecular Oncology, EarlyView.
Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski, Liudmyla Dolinchuk, Michał Jerzak, Albert Gandurski, Tomasz Grochowski, Weronika Wojtyś, Maciej Zadrożny, Wojciech Kaźmierczak, Małgorzata Lenarcik, Marta Matejak‐Górska, Radosław Samsel, Tomasz Olesiński, Dawid Walerych   +12 more
wiley   +1 more source

On-line learning of shape information for object segmentation and tracking [PDF]

, 2009
We present segmentation and tracking of deformable objects using non-linear on-line learning of high-level shape information in the form of a level set function.
Chiverton, John, John, Chiverton, John Chiverton, Xianghua Xie, Xie, Xianghua, Majid Mirmehdi, Mirmehdi, Majid, Xianghua, Xie   +7 more
core   +1 more source