Zobrazeno 1 - 10
of 1 278 023
pro vyhledávání: '"A. A. Ahmed"'
Object detection is crucial in various cutting-edge applications, such as autonomous vehicles and advanced robotics systems, primarily relying on data from conventional frame-based RGB sensors. However, these sensors often struggle with issues like m
Externí odkaz:
http://arxiv.org/abs/2408.05321
Autor:
Marcel, Miracle Chibuzor, Diaby, Kassamba Abdel Aziz, Guennoun, Meryem, Nabifo, Betty Rose, Elattar, Mohamed, Rajaonarivelo, Andoniaina, Pius, Privatus, Kgobathe, Molly Nkamogelang, Luis, Immanuel, Shilunga, Sigrid, Etteyeb, Nejmeddine, Qhomane, Keketso, Nyangi, Samuel, Kalunga, Tresford Chilufya, Assano, Nunes Alfredo, Jequecene, Edson Domingos, Joseph, Mafuka Lusala, Sudum, Esaenwi, Gerald, Jorbedom Leelabari, Gore, Christopher Tombe Louis, Hosny, Kareem Waleed, Yasser, Nagat, Franck, Jocelyn, Kourouma, Mamoudou, Bobb, Baboucarr, Jaiteh, Kebab, Sylla, Salma, Obame, Hans Essone, Kiyeng, Dennis, Ngwanw, Thobekile Sandra, Simon, Tawanda Kelvin, Sulayman, Saja Alhoush, Regaibi, Salma, Yahaya, Souley, Ornela, Tengwi Mogou, Viyuyi, Henry Sanderson, Matambo, Fortune Tatenda, Asare-Darko, Matthias, Gbaba, Christian Kontoa Koussouwa, da Silva, Moisés, Joseph, Ntahompagaze, Gomes, Gilberto, Mkhabela, Bongiwe Portia, Bvumbwe, Bauleni, Nkhowani, Tshombe, Gahou, Mawugnon Axel, Abotsi-Masters, Sarah, Simbizi, René, Mugisha, Salomon, Saeed, Ahmed, Eldaw, Mohammed Yahya Alradi, Thomas, Allen, ridha, Ben Abdallah, kaseha, Dieumerci, Baradei, Sherine Ahmed El, Hussein, Nahla Hazem, Fabrice, Bado, Anekwe, Ngozika Frances, Ramessur, Arvind, Koroma, Mohamed Ali, Safary, Harold, Leonardo, Oosthuizen, Dlamini, Mdumiseni Wisdom Dabulizwe, Djabbi, Mamadou Mahamat, Angela, Nonofo, Jalloh, Mamaja, Balde, Mamadou, Olayiwola, Joy, Ibharalu, Elijah, Tchangole, Thierry Martial, Memberu, Kirubel, Dinsa, Lidia, Ezeakunne, Chidozie Gospel
Asteroid search is a global effort for planetary defense. The International Astronomical Search Collaboration (IASC) is the leading global educational outreach program that provides high-quality astronomical datasets to citizen scientists to discover
Externí odkaz:
http://arxiv.org/abs/2408.03385
Autor:
Mahboob, Mariyam, Ahmed, Mohammed Rayyan Uddin, Zia, Zoiba, Ali, Mariam Shakeel, Ahmed, Ayman Khaleel
The advent of Artificial intelligence has promising advantages that can be utilized to transform the landscape of software project development. The Software process framework consists of activities that constantly require routine human interaction, l
Externí odkaz:
http://arxiv.org/abs/2408.00703
Quantum devices need precise control to achieve their full capability. In this work, we address the problem of controlling closed quantum systems, tackling two main issues. First, in practice the control signals are usually subject to unknown classic
Externí odkaz:
http://arxiv.org/abs/2407.09877
Autor:
Elhenawy, Mohammed, Abutahoun, Ahmad, Alhadidi, Taqwa I., Jaber, Ahmed, Ashqar, Huthaifa I., Jaradat, Shadi, Abdelhay, Ahmed, Glaser, Sebastien, Rakotonirainy, Andry
Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems, including zero-shot in-context learning scenarios. This study explores the ability of MLLMs in visually solv
Externí odkaz:
http://arxiv.org/abs/2407.00092
The increasing reliance on online recruitment platforms coupled with the adoption of AI technologies has highlighted the critical need for efficient resume classification methods. However, challenges such as small datasets, lack of standardized resum
Externí odkaz:
http://arxiv.org/abs/2406.18125
Autor:
Palaskar, Shruti, Rudovic, Oggi, Dharur, Sameer, Pesce, Florian, Krishna, Gautam, Sivaraman, Aswin, Berkowitz, Jack, Abdelaziz, Ahmed Hussen, Adya, Saurabh, Tewfik, Ahmed
Although Large Language Models (LLMs) have shown promise for human-like conversations, they are primarily pre-trained on text data. Incorporating audio or video improves performance, but collecting large-scale multimodal data and pre-training multimo
Externí odkaz:
http://arxiv.org/abs/2406.09617
Autor:
Elhenawy, Mohammed, Abdelhay, Ahmed, Alhadidi, Taqwa I., Ashqar, Huthaifa I, Jaradat, Shadi, Jaber, Ahmed, Glaser, Sebastien, Rakotonirainy, Andry
Multimodal Large Language Models (MLLMs) have demonstrated proficiency in processing di-verse modalities, including text, images, and audio. These models leverage extensive pre-existing knowledge, enabling them to address complex problems with minima
Externí odkaz:
http://arxiv.org/abs/2406.06865
This study thoroughly investigates how well deep learning models can recognize Arabic handwritten text for person biometric identification. It compares three advanced architectures -- ResNet50, MobileNetV2, and EfficientNetB7 -- using three widely re
Externí odkaz:
http://arxiv.org/abs/2406.00409
Autor:
Choudhary, Lalita, Ahmed, Anees
The phase diagram of the Gross-Neveu model in 1+1 dimensions is studied using Ginzburg-Landau expansion. It predicts several features of the exact phase diagram correctly even at low orders. It is shown that increasing the order of the expansion impr
Externí odkaz:
http://arxiv.org/abs/2408.08755