Zobrazeno 1 - 10
of 15 692
pro vyhledávání: '"Gomaa AS"'
Autor:
Gomaa, Amr, Mahdy, Bilal
Integration of human feedback plays a key role in improving the learning capabilities of intelligent systems. This comparative study delves into the performance, robustness, and limitations of imitation learning compared to traditional reinforcement
Externí odkaz:
http://arxiv.org/abs/2410.21403
Autor:
Elshaarawy, Mohamed, Saeed, Ashrakat, Sheta, Mariam, Said, Abdelrahman, Bakr, Asem, Bahaa, Omar, Gomaa, Walid
This paper proposes a machine learning approach for classifying classical and new Egyptian music by composer and generating new similar music. The proposed system utilizes a convolutional neural network (CNN) for classification and a CNN autoencoder
Externí odkaz:
http://arxiv.org/abs/2410.19719
The increasing integration of machine learning across various domains has underscored the necessity for accessible systems that non-experts can utilize effectively. To address this need, the field of automated machine learning (AutoML) has developed
Externí odkaz:
http://arxiv.org/abs/2410.17469
The rapid expansion of video content across a variety of industries, including social media, education, entertainment, and surveillance, has made video summarization an essential field of study. The current work is a survey that explores the various
Externí odkaz:
http://arxiv.org/abs/2410.04449
Metal manufacturing often results in the production of defective products, leading to operational challenges. Since traditional manual inspection is time-consuming and resource-intensive, automatic solutions are needed. The study utilizes deep learni
Externí odkaz:
http://arxiv.org/abs/2410.04440
Autor:
Shokry, Ahmed, Gomaa, Walid, Zaenker, Tobias, Dawood, Murad, Maged, Shady A., Awad, Mohammed I., Bennewitz, Maren
Peg-in-hole assembly in unknown environments is a challenging task due to onboard sensor errors, which result in uncertainty and variations in task parameters such as the hole position and orientation. Meta Reinforcement Learning (Meta RL) has been p
Externí odkaz:
http://arxiv.org/abs/2409.16208
Autor:
Huang, Yixing, Fan, Fuxin, Gomaa, Ahmed, Maier, Andreas, Fietkau, Rainer, Bert, Christoph, Putz, Florian
Cone-beam computed tomography (CBCT) is widely used in interventional surgeries and radiation oncology. Due to the limited size of flat-panel detectors, anatomical structures might be missing outside the limited field-of-view (FOV), which restricts t
Externí odkaz:
http://arxiv.org/abs/2409.08800
Traditional fish farming practices often lead to inefficient feeding, resulting in environmental issues and reduced productivity. We developed an innovative system combining computer vision and IoT technologies for precise Tilapia feeding. Our soluti
Externí odkaz:
http://arxiv.org/abs/2409.08695
Publikováno v:
Foundations and Trends in Information Systems: Vol. 7: No. 4, pp 310-356 (2024)
This paper provides a comprehensive analysis of the challenges and controversies associated with blockchain technology. It identifies technical challenges such as scalability, security, privacy, and interoperability, as well as business and adoption
Externí odkaz:
http://arxiv.org/abs/2409.06179
Robust frame-wise embeddings are essential to perform video analysis and understanding tasks. We present a self-supervised method for representation learning based on aligning temporal video sequences. Our framework uses a transformer-based encoder t
Externí odkaz:
http://arxiv.org/abs/2409.04607