Zobrazeno 1 - 10
of 37
pro vyhledávání: '"ERAQI, HESHAM M."'
Autor:
Sulaiman, Marwah, Shehabeldin, Zahraa, Fahmy, Israa, Barakat, Mohammed, El-Naggar, Mohammed, Hussein, Dareen, Youssef, Moustafa, Eraqi, Hesham M.
Recently, video super resolution (VSR) has become a very impactful task in the area of Computer Vision due to its various applications. In this paper, we propose Recurrent Back-Projection Generative Adversarial Network (RBPGAN) for VSR in an attempt
Externí odkaz:
http://arxiv.org/abs/2311.09178
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems
Conditional imitation learning (CIL) trains deep neural networks, in an end-to-end manner, to mimic human driving. This approach has demonstrated suitable vehicle control when following roads, avoiding obstacles, or taking specific turns at intersect
Externí odkaz:
http://arxiv.org/abs/2211.11579
In this work, we propose a technique to transfer speech recognition capabilities from audio speech recognition systems to visual speech recognizers, where our goal is to utilize audio data during lipreading model training. Impressive progress in the
Externí odkaz:
http://arxiv.org/abs/2207.05692
Publikováno v:
2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS 2022), Larnaca, Cyprus
Collision avoidance systems play a vital role in reducing the number of vehicle accidents and saving human lives. This paper extends the previous work using evolutionary neural networks for reactive collision avoidance. We are proposing a new method
Externí odkaz:
http://arxiv.org/abs/2203.15522
The largest dataset of Arabic speech mispronunciation detections in Egyptian dialogues is introduced. The dataset is composed of annotated audio files representing the top 100 words that are most frequently used in the Arabic language, pronounced by
Externí odkaz:
http://arxiv.org/abs/2111.01136
Autor:
Mohamed, Amr S., Abdelkader, Ali, Anany, Mohamed, El-Behady, Omar, Faisal, Muhammad, Hangal, Asser, Eraqi, Hesham M., Moustafa, Mohamed N.
LiDARs and cameras are the two main sensors that are planned to be included in many announced autonomous vehicles prototypes. Each of the two provides a unique form of data from a different perspective to the surrounding environment. In this paper, w
Externí odkaz:
http://arxiv.org/abs/2108.07661
Autor:
Elashmawy, Shahd, Ramsis, Marian, Eraqi, Hesham M., Eldeshnawy, Farah, Mabrouk, Hadeel, Abugabal, Omar, Sakr, Nourhan
Despite the advancement in the domain of audio and audio-visual speech recognition, visual speech recognition systems are still quite under-explored due to the visual ambiguity of some phonemes. In this work, we propose a new lip-reading model that c
Externí odkaz:
http://arxiv.org/abs/2108.03543
Autor:
Ibrahim, Ahmed, El-Refai, Ayman, Ahmed, Sara, Aboul-Ela, Mariam, Eraqi, Hesham M., Moustafa, Mohamed
Due to the mass advancement in ubiquitous technologies nowadays, new pervasive methods have come into the practice to provide new innovative features and stimulate the research on new human-computer interactions. This paper presents a hand gesture re
Externí odkaz:
http://arxiv.org/abs/2108.02148
Advanced sensors are a key to enable self-driving cars technology. Laser scanner sensors (LiDAR, Light Detection And Ranging) became a fundamental choice due to its long-range and robustness to low light driving conditions. The problem of designing a
Externí odkaz:
http://arxiv.org/abs/1907.07748
Publikováno v:
Journal of Advanced Transportation, Machine Learning in Transportation (MLT) Issue, 2019
The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasing over the last few years. Nearly fifth of these accidents are caused by distracted drivers.
Externí odkaz:
http://arxiv.org/abs/1901.09097