Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Iman Soltani"'
Autor:
Ehsan Kazemi, Iman Soltani
Publikováno v:
Transportation Research Interdisciplinary Perspectives, Vol 27, Iss , Pp 101213- (2024)
The safety of work zones is a critical issue for drivers, transportation agencies, and governing authorities. In particular, the vehicles that perform lane changes in the proximity of the work zones involving lane closure, pose a significant threat t
Externí odkaz:
https://doaj.org/article/385680f78207463597df50c9e603306f
Autor:
Arina Nisanova, BA, Arefeh Yavary, MSc, Jordan Deaner, MD, Ferhina S. Ali, MD, MPH, Priyanka Gogte, MD, Richard Kaplan, MD, Kevin C. Chen, MD, Eric Nudleman, MD, PhD, Dilraj Grewal, MD, Meenakashi Gupta, MD, Jeremy Wolfe, MD, Michael Klufas, MD, Glenn Yiu, MD, PhD, Iman Soltani, PhD, Parisa Emami-Naeini, MD, MPH
Publikováno v:
Ophthalmology Science, Vol 4, Iss 5, Pp 100470- (2024)
Purpose: Automated machine learning (AutoML) has emerged as a novel tool for medical professionals lacking coding experience, enabling them to develop predictive models for treatment outcomes. This study evaluated the performance of AutoML tools in d
Externí odkaz:
https://doaj.org/article/15a7f54b929744708a86d399eab9496a
Publikováno v:
Polymers, Vol 15, Iss 24, p 4714 (2023)
Solvent-based and mechanical recycling technology approaches were compared with respect to each process’s decontamination efficiency. Herein, post-consumer polystyrene (PS) feedstock was recycled by both technologies, yielding recycled PS resins (r
Externí odkaz:
https://doaj.org/article/18db5b2f735d4dbea286049b6583e9c6
Autor:
Debo Shi, Alireza Rahimpour, Amin Ghafourian, Mohammad Mahdi Naddaf Shargh, Devesh Upadhyay, Ty A. Lasky, Iman Soltani
Publikováno v:
Sensors, Vol 23, Iss 13, p 6107 (2023)
Pose estimation is crucial for automating assembly tasks, yet achieving sufficient accuracy for assembly automation remains challenging and part-specific. This paper presents a novel, streamlined approach to pose estimation that facilitates automatio
Externí odkaz:
https://doaj.org/article/830442d115544f3e905c367a61acb620
Autor:
Ghafourian, Amin, Shui, Huanyi, Upadhyay, Devesh, Gupta, Rajesh, Filev, Dimitar, Bozchalooi, Iman Soltani
Autoencoders have been extensively used in the development of recent anomaly detection techniques. The premise of their application is based on the notion that after training the autoencoder on normal training data, anomalous inputs will exhibit a si
Externí odkaz:
http://arxiv.org/abs/2306.12627
Autor:
Fahimeh Kamarei, Farshid Movaghari, Alireza Ghaffari, Iman Soltani Bozchalooi, Ali Zamani, Ali Jabbari
Publikováno v:
Arabian Journal of Chemistry, Vol 7, Iss 6, Pp 1079-1085 (2014)
In this study an effective method was developed to assay erythromycin ethylsuccinate for an oral suspension dosage form. The chromatographic separation was achieved on an X-Terra™ C18 analytical column. A mixture of acetonitrile–ammonium dihydrog
Externí odkaz:
https://doaj.org/article/9c08a13915f14053970fbbda12bd8982
The performance of applications that require frame rendering time estimation or dynamic frequency scaling, rely on the accuracy of the workload model that is utilized within these applications. Existing models lack sufficient accuracy in their core m
Externí odkaz:
http://arxiv.org/abs/2204.11025
We study the problem of semi-supervised anomaly detection with domain adaptation. Given a set of normal data from a source domain and a limited amount of normal examples from a target domain, the goal is to have a well-performing anomaly detector in
Externí odkaz:
http://arxiv.org/abs/2006.03689
In this paper, we present a memory-augmented algorithm for anomaly detection. Classical anomaly detection algorithms focus on learning to model and generate normal data, but typically guarantees for detecting anomalous data are weak. The proposed Mem
Externí odkaz:
http://arxiv.org/abs/2002.02669
In this paper, we investigate algorithms for anomaly detection. Previous anomaly detection methods focus on modeling the distribution of non-anomalous data provided during training. However, this does not necessarily ensure the correct detection of a
Externí odkaz:
http://arxiv.org/abs/2001.06591