Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Dawoud, Youssef"'
Neural architecture search automates the design of neural network architectures usually by exploring a large and thus complex architecture search space. To advance the architecture search, we present a graph diffusion-based NAS approach that uses dis
Externí odkaz:
http://arxiv.org/abs/2403.06020
Generalisation of deep neural networks becomes vulnerable when distribution shifts are encountered between train (source) and test (target) domain data. Few-shot domain adaptation mitigates this issue by adapting deep neural networks pre-trained on t
Externí odkaz:
http://arxiv.org/abs/2308.04946
In microscopy image cell segmentation, it is common to train a deep neural network on source data, containing different types of microscopy images, and then fine-tune it using a support set comprising a few randomly selected and annotated training ta
Externí odkaz:
http://arxiv.org/abs/2211.10244
Deep neural networks currently deliver promising results for microscopy image cell segmentation, but they require large-scale labelled databases, which is a costly and time-consuming process. In this work, we relax the labelling requirement by combin
Externí odkaz:
http://arxiv.org/abs/2208.02105
Autor:
Holzbock, Adrian, Tsaregorodtsev, Alexander, Dawoud, Youssef, Dietmayer, Klaus, Belagiannis, Vasileios
Publikováno v:
2022 IEEE Intelligent Vehicles Symposium (IV), June 5th - 9th, 2022, Aachen, Germany, pp. 1099-1106
Gesture recognition is essential for the interaction of autonomous vehicles with humans. While the current approaches focus on combining several modalities like image features, keypoints and bone vectors, we present neural network architecture that d
Externí odkaz:
http://arxiv.org/abs/2204.11511
Autor:
Rudolph, Michael, Dawoud, Youssef, Güldenring, Ronja, Nalpantidis, Lazaros, Belagiannis, Vasileios
We present a lightweight encoder-decoder architecture for monocular depth estimation, specifically designed for embedded platforms. Our main contribution is the Guided Upsampling Block (GUB) for building the decoder of our model. Motivated by the con
Externí odkaz:
http://arxiv.org/abs/2203.04206
Automatic cell segmentation in microscopy images works well with the support of deep neural networks trained with full supervision. Collecting and annotating images, though, is not a sustainable solution for every new microscopy database and cell typ
Externí odkaz:
http://arxiv.org/abs/2007.01671
Autor:
Nguyen, Cuong C., Dawoud, Youssef, Do, Thanh-Toan, Nascimento, Jacinto C., Belagiannis, Vasileios, Carneiro, Gustavo
Publikováno v:
In Meta Learning With Medical Imaging and Health Informatics Applications 2023:185-209
Autor:
Amatriain, Xavier, Balaji, Yogesh, Bekiranov, Stefan, Belagiannis, Vasileios, Benyoussef, Anas-Alexis, Carneiro, Gustavo, Chablani, Manish, Chen, Cheng, Cho, Hyun Jae, Chou, Jingyuan, Cochener, Béatrice, Conze, Pierre-Henri, Dawoud, Youssef, Do, Thanh-Toan, Dou, Qi, Farshad, Azade, Fu, Chi-Wing, Guha Roy, Abhijit, Guo, Pengfei, Heng, Pheng-Ann, Hoang, Hieu, Jiang, Shanshan, Jin, Yueming, Kannan, Anitha, Kim, Jieum, Lamard, Mathieu, Le, Ngan, Le Callet, Patrick, Le Guilcher, Alexandre, Li, Xiaomeng, Ling, Suiyi, Liu, Quande, Massin, Pascale, Matta, Sarah, Mobiny, Aryan, Nascimento, Jacinto C., Navab, Nassir, Nguyen, Cuong C., Nguyen, Hien Van, Pastor, Andreas, Patel, Vishal M., Paul, Angshuman, Pölsterl, Sebastian, Prabhu, Viraj, Quellec, Gwenolé, Ravuri, Murali, Ricquebourg, Vincent, Rottier, Jean-Bernard, Sankaranarayanan, Swami, Shen, Thomas C., Siddiqui, Shayan, Sontag, David, Summers, Ronald M., Suo, Qiuling, Tang, Yu-Xing, Tran, Minh-Triet, Vo-Ho, Viet-Khoa, Wachinger, Christian, Wang, Puyang, Xing, Lei, Yamazaki, Kashu, Yeganeh, Yousef, Yu, Lequan, Yuan, Pengyu, Zang, Chongzhi, Zhang, Aidong, Zhou, Jinyuan
Publikováno v:
In Meta Learning With Medical Imaging and Health Informatics Applications 2023:xv-xix