Zobrazeno 1 - 10
of 215
pro vyhledávání: '"Talebpour, Alireza"'
Autor:
Radvand, Tina, Talebpour, Alireza
Electric vehicles (EVs) play a significant role in enhancing the sustainability of transportation systems. However, their widespread adoption is hindered by inadequate public charging infrastructure, particularly to support long-distance travel. Iden
Externí odkaz:
http://arxiv.org/abs/2410.16231
Due to the inherent safety concerns associated with traffic movement in unconstrained two-dimensional settings, it is important that pedestrians' and other modes' movements such as bicyclists are modeled as a risk-taking stochastic dynamic process th
Externí odkaz:
http://arxiv.org/abs/2407.19172
Coreference resolution, critical for identifying textual entities referencing the same entity, faces challenges in pronoun resolution, particularly identifying pronoun antecedents. Existing methods often treat pronoun resolution as a separate task fr
Externí odkaz:
http://arxiv.org/abs/2405.10714
Autor:
Ammourah, Rami, Talebpour, Alireza
A multi-agent deep reinforcement learning-based framework for traffic shaping. The proposed framework offers a key advantage over existing congestion management strategies which is the ability to mitigate hysteresis phenomena. Unlike existing congest
Externí odkaz:
http://arxiv.org/abs/2302.03141
Pronoun resolution is a challenging subset of an essential field in natural language processing called coreference resolution. Coreference resolution is about finding all entities in the text that refers to the same real-world entity. This paper pres
Externí odkaz:
http://arxiv.org/abs/2211.06257
Coreference resolution (CR), identifying expressions referring to the same real-world entity, is a fundamental challenge in natural language processing (NLP). This paper explores the latest advancements in CR, spanning coreference and anaphora resolu
Externí odkaz:
http://arxiv.org/abs/2211.04428
Undoubtedly, textural property of an image is one of the most important features in object recognition task in both human and computer vision applications. Here, we investigated the neural signatures of four well-known statistical texture features in
Externí odkaz:
http://arxiv.org/abs/2111.09118
Publikováno v:
In Expert Systems With Applications 15 August 2023 224
This study proposes a deep learning methodology to predict the propagation of traffic shockwaves. The input to the deep neural network is time-space diagram of the study segment, and the output of the network is the predicted (future) propagation of
Externí odkaz:
http://arxiv.org/abs/1905.02197
Image semantic segmentation is parsing image into several partitions in such a way that each region of which involves a semantic concept. In a weakly supervised manner, since only image-level labels are available, discriminating objects from the back
Externí odkaz:
http://arxiv.org/abs/1902.04356