Výsledky vyhledávání - "Toosi, Ramin"

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CNN Autoencoder Resizer: A Power-Efficient LoS/NLoS Detector in MIMO-enabled UAV Networks

Autor: Akhtarshenas, Azim, Ayoobi, Navid, Lopez-Perez, David, Toosi, Ramin, Amoozadeh, Matin

Optimizing the design, performance, and resource efficiency of wireless networks (WNs) necessitates the ability to discern Line of Sight (LoS) and Non-Line of Sight (NLoS) scenarios across diverse applications and environments. Unmanned Aerial Vehicl

Externí odkaz: http://arxiv.org/abs/2405.16697

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Brand Visibility in Packaging: A Deep Learning Approach for Logo Detection, Saliency-Map Prediction, and Logo Placement Analysis

Autor: Hosseini, Alireza, Hooshanfar, Kiana, Omrani, Pouria, Toosi, Reza, Toosi, Ramin, Ebrahimian, Zahra, Akhaee, Mohammad Ali

In the highly competitive area of product marketing, the visibility of brand logos on packaging plays a crucial role in shaping consumer perception, directly influencing the success of the product. This paper introduces a comprehensive framework to m

Externí odkaz: http://arxiv.org/abs/2403.02336

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Information Modified K-Nearest Neighbor

Autor: Vahedifar, Mohammad Ali, Akhtarshenas, Azim, Sabbaghian, Maryam, Rafatpanah, Mohammad Mohammadi, Toosi, Ramin

The fundamental concept underlying K-Nearest Neighbors (KNN) is the classification of samples based on the majority through their nearest neighbors. Although distance and neighbors' labels are critical in KNN, traditional KNN treats all samples equal

Externí odkaz: http://arxiv.org/abs/2312.01991

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Unsupervised Representations Improve Supervised Learning in Speech Emotion Recognition

Autor: Tehrani, Amirali Soltani, Faridani, Niloufar, Toosi, Ramin

Speech Emotion Recognition (SER) plays a pivotal role in enhancing human-computer interaction by enabling a deeper understanding of emotional states across a wide range of applications, contributing to more empathetic and effective communication. Thi

Externí odkaz: http://arxiv.org/abs/2309.12714

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Soccer Event Detection Using Deep Learning

Autor: Karimi, Ali, Toosi, Ramin, Akhaee, Mohammad Ali

Event detection is an important step in extracting knowledge from the video. In this paper, we propose a deep learning approach to detect events in a soccer match emphasizing the distinction between images of red and yellow cards and the correct dete

Externí odkaz: http://arxiv.org/abs/2102.04331

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Face Manifold: Manifold Learning for Synthetic Face Generation

Autor: Dinashi, Kimia, Toosi, Ramin, Akhaee, Mohammad Ali

Face is one of the most important things for communication with the world around us. It also forms our identity and expressions. Estimating the face structure is a fundamental task in computer vision with applications in different areas such as face

Externí odkaz: http://arxiv.org/abs/1910.01403

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