Zobrazeno 1 - 10
of 402
pro vyhledávání: '"Acton, Scott T."'
Automatic cell tracking in dense environments is plagued by inaccurate correspondences and misidentification of parent-offspring relationships. In this paper, we introduce a novel cell tracking algorithm named DenseTrack, which integrates deep learni
Externí odkaz:
http://arxiv.org/abs/2406.19574
This paper presents a novel spatiotemporal transformer network that introduces several original components to detect actions in untrimmed videos. First, the multi-feature selective semantic attention model calculates the correlations between spatial
Externí odkaz:
http://arxiv.org/abs/2405.08204
Autor:
Guha, Soumee, Acton, Scott T.
Coherent imaging systems, such as medical ultrasound and synthetic aperture radar (SAR), are subject to corruption from speckle due to sub-resolution scatterers. Since speckle is multiplicative in nature, the constituent image regions become corrupte
Externí odkaz:
http://arxiv.org/abs/2311.10868
Publikováno v:
Pattern Recognition 2023
This paper proposes a novel multi-modal transformer network for detecting actions in untrimmed videos. To enrich the action features, our transformer network utilizes a new multi-modal attention mechanism that computes the correlations between differ
Externí odkaz:
http://arxiv.org/abs/2305.19624
Publikováno v:
Pattern Recognition 2023
This paper proposes a novel age estimation algorithm, the Temporally-Aware Adaptive Graph Convolutional Network (TAA-GCN). Using a new representation based on graphs, the TAA-GCN utilizes skeletal, posture, clothing, and facial information to enrich
Externí odkaz:
http://arxiv.org/abs/2305.08779
Publikováno v:
In Computers and Education: Artificial Intelligence June 2024 6
Publikováno v:
In Expert Systems With Applications 15 March 2024 238 Part D
This study proposes an efficient neural network with convolutional layers to classify significantly class-imbalanced clinical data. The data are curated from the National Health and Nutritional Examination Survey (NHANES) with the goal of predicting
Externí odkaz:
http://arxiv.org/abs/1909.00489
Autor:
Sadeghzadehyazdi, Nasrin, Batabyal, Tamal, Dhar, Nibir K., Familoni, B. O., Iftekharuddin, K. M., Acton, Scott T.
Gait recognition using noninvasively acquired data has been attracting an increasing interest in the last decade. Among various modalities of data sources, it is experimentally found that the data involving skeletal representation are amenable for re
Externí odkaz:
http://arxiv.org/abs/1905.07058
Autor:
Sadeghzadehyazdi, Nasrin, Batabyal, Tamal, Glandon, A., Dhar, Nibir K., Familoni, B. O., Iftekharuddin, K. M., Acton, Scott T.
Gait recognition is a leading remote-based identification method, suitable for real-world surveillance and medical applications. Model-based gait recognition methods have been particularly recognized due to their scale and view-invariant properties.
Externí odkaz:
http://arxiv.org/abs/1905.00943