Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Munir, Mohsin"'
Autor:
Wörmann, Julian, Bogdoll, Daniel, Brunner, Christian, Bührle, Etienne, Chen, Han, Chuo, Evaristus Fuh, Cvejoski, Kostadin, van Elst, Ludger, Gottschall, Philip, Griesche, Stefan, Hellert, Christian, Hesels, Christian, Houben, Sebastian, Joseph, Tim, Keil, Niklas, Kelsch, Johann, Keser, Mert, Königshof, Hendrik, Kraft, Erwin, Kreuser, Leonie, Krone, Kevin, Latka, Tobias, Mattern, Denny, Matthes, Stefan, Motzkus, Franz, Munir, Mohsin, Nekolla, Moritz, Paschke, Adrian, von Pilchau, Stefan Pilar, Pintz, Maximilian Alexander, Qiu, Tianming, Qureishi, Faraz, Rizvi, Syed Tahseen Raza, Reichardt, Jörg, von Rueden, Laura, Sagel, Alexander, Sasdelli, Diogo, Scholl, Tobias, Schunk, Gerhard, Schwalbe, Gesina, Shen, Hao, Shoeb, Youssef, Stapelbroek, Hendrik, Stehr, Vera, Srinivas, Gurucharan, Tran, Anh Tuan, Vivekanandan, Abhishek, Wang, Ya, Wasserrab, Florian, Werner, Tino, Wirth, Christian, Zwicklbauer, Stefan
The availability of representative datasets is an essential prerequisite for many successful artificial intelligence and machine learning models. However, in real life applications these models often encounter scenarios that are inadequately represen
Externí odkaz:
http://arxiv.org/abs/2205.04712
Two-stage detectors are state-of-the-art in object detection as well as pedestrian detection. However, the current two-stage detectors are inefficient as they do bounding box regression in multiple steps i.e. in region proposal networks and bounding
Externí odkaz:
http://arxiv.org/abs/2203.02331
With the advent of machine learning in applications of critical infrastructure such as healthcare and energy, privacy is a growing concern in the minds of stakeholders. It is pivotal to ensure that neither the model nor the data can be used to extrac
Externí odkaz:
http://arxiv.org/abs/2111.14838
Autor:
Palacio, Sebastian, Lucieri, Adriano, Munir, Mohsin, Hees, Jörn, Ahmed, Sheraz, Dengel, Andreas
Publikováno v:
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision (ICCV) Workshops
The field of explainable AI (XAI) has quickly become a thriving and prolific community. However, a silent, recurrent and acknowledged issue in this area is the lack of consensus regarding its terminology. In particular, each new contribution seems to
Externí odkaz:
http://arxiv.org/abs/2105.06677
Autor:
Munir, Mohsin, Siddiqui, Shoaib Ahmed, Küsters, Ferdinand, Mercier, Dominique, Dengel, Andreas, Ahmed, Sheraz
Neural networks (NN) are considered as black-boxes due to the lack of explainability and transparency of their decisions. This significantly hampers their deployment in environments where explainability is essential along with the accuracy of the sys
Externí odkaz:
http://arxiv.org/abs/1905.06175
Publikováno v:
IEEE Access 2019 PP(99):1-1
This paper presents a novel framework for demystification of convolutional deep learning models for time-series analysis. This is a step towards making informed/explainable decisions in the domain of time-series, powered by deep learning. There have
Externí odkaz:
http://arxiv.org/abs/1802.02952
Publikováno v:
Regional Anesthesia and Acute Pain Management. 16:103-114
Articaine is an intermediate-potency and short-acting amide local anesthetic with a fast metabolism due to an ester group in its structure. Articaine was widely used in dental practice, but now has an effective form for surgical and anesthetic use. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8087fa22ecc6c04aafc461323e1ffbae
https://doi.org/10.17816/1993-6508-2022-16-1-103-114
https://doi.org/10.17816/1993-6508-2022-16-1-103-114
Akademický článek
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Autor:
Khalid, Nabeel, Schmeisser, Fabian, Mohammadmahdi Koochali, Munir, Mohsin, Edlund, Christoffer, Jackson, Timothy, Trygg, Johan, Sjögren, Rickard, Dengel, Andreas, Sheraz Ahmed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b737b5a8fa29d145a83fbbfe43011d56