informatik-vortraege Mai 2024

informatik-vortraege@lists.rwth-aachen.de

3 Teilnehmer
5 Diskussionen

Einladung Informatik Oberseminar Lubna Ali

von Bombelka, Angelika

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Dienstag, 30. Januar 2024, 14.00 Uhr Ort: 9222, E3, Ahornstr. 55 und hybrid via Zoom (https://rwth.zoom-x.de/j/64937773189?pwd=eGttNUMzSElnQUVkc3FrYzBqK2F4UT09) Referent: Lubna Ali M.Sc. RWTH Lehr- und Forschungsgebiet Informatik 9 (Lerntechnologien) Thema: convOERter: A Technical Assistance Tool to Support Semi-Automatic Conversion of Images in Educational Materials as OER Abstract: Open Educational Resources (OER) are seen as an important element in the process of digitizing higher education teaching and as essential building blocks for openness in education. They can be defined as teaching, learning, and research materials that have been made openly available, shareable, and modifiable. OER include different types of resources such as full courses, textbooks, videos, presentations, tests, and images, which are usually published under the open Creative Commons licences. OER can play an important role in improving education by facilitating access to high quality digital educational materials. Accordingly, there is a steady increase among higher education institutions to participate in the so-called "open movement" in general and in utilizing OER in particular. Nevertheless, there are many challenges that still face the deployment of OER in the educational context. One of the main challenges is the production of new OER materials and converting already existing materials into OER, which could be viable by qualifying educators through training courses and/or supporting them with specific tools. There are many platforms and tools that support the creation of new OER content. However, to our knowledge, there are no tools that perform fully- or semi-automatic conversion of already existing educational materials. This identified gap was the basis for the design and implementation of the OER conversion tool (convOERter). The tool supports the user by semi-automatically converting educational materials containing images into OER-compliant materials. The main functionality of the tool is based on reading a file, extracting all images as well as all possible metadata, and substituting the extracted images with OER elements in a semi-automated way. The retrieved OER images are referenced and licenced properly according to the known TASLL rule. Finally, the entire file is automatically licenced under Creative Commons excluding specific elements from the entire licence such as logos. In order to evaluate the effectiveness of the tool in promoting the use of OER, a comprehensive user study was conducted with educators and OER enthusiastic at different universities. The study was accomplished by offering a series of OER evaluation workshops to compare the conversion efficiency of the tool with manual conversion. The results show that using the conversion tool improves the conversion process in terms of speed, license quality, and total efficiency. These results highlight that the tool can be a valuable addition to the community, especially for users less experienced with OER. As a future work, it is intended to further develop the tool and improve its functionality. Additionally, a long-term study can be conducted to assess the impact of the tool in facilitating and enhancing the production of OER on a larger scale. Es laden ein: die Dozentinnen und Dozenten der Informatik

3 Wochen, 1 Tag

Einladung: Informatik-Oberseminar Sabarinath Mahadevan

von Mahadevan, Sabarinath

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Freitag, 24. Mai 2024, 10.30 Uhr Ort: Raum 025, Mies-van-der-Rohe Str. 15 (UMIC Gebäude) Der Vortrag findet hybrid statt. Zoom: https://rwth.zoom-x.de/j/64536789621?pwd=d2I5Y1VDM2xscVVDbTF0ZnJVWUUvZz09 Meeting ID: 645 3678 9621, Passcode: 998171 Referent: Sabarinath Mahadevan, M.Sc. Lehrstuhl Informatik 13 Thema: The Many Facets of Object Segmentation in Images and Videos Abstract: Segmentation is an important task in computer vision where the pixels belonging to a region of interest, that often share similar characteristics, have to be separated out, and assigned a unique label. This task is relevant in both the image and video domains, and finds direct applications in a wide range of fields including but not limited to autonomous driving, robotics, image editing, and surveillance. For both images and videos, the task of segmentation has various flavours that are often highly related and equally challenging. With the advent of deep learning, modern computer vision algorithms are able to leverage large amounts of available data to achieve impressive performance for many of these segmentation problems. However, such algorithms are often catered either towards segmenting a pre-defined set of object categories, or to some specific sub-domains, and require to be adapted for out-of-domain tasks by training these methods on additional domain-specific data, that is expensive to annotate. As a result, we need algorithms that generalise well to data from unseen domains and also to new task settings in addition to having methods that can efficiently annotate data. The first part of this thesis focusses on efficiently annotating objects using Interactive Segmentation, where the goal is to segment and refine objects in an image using user clicks. Here, I'll present two of our research works that advances the state-of-the-art in the interactive segmentation domain. The first among these, ITIS, develops a novel iterative training strategy in which clicks are added iteratively during training based on the error regions in the network predictions. The iterative training strategy aligns the simulated user-click patterns that are used during training with the actual click patterns that the network would encounter at test time. While this strategy is effective in reducing the number of clicks required to annotate objects, ITIS can only segment one object at a time due to the limitations of its network architecture. We address this problem in our subsequent work called DynaMITe, where we formulate user clicks as spatiotemporal sequences, and develop a novel Transformer based formulation that can process such a sequence and encode them into relevant object or region descriptors. These descriptors are then used to generate the relevant instance segmentation masks. Unlike previous methods, our architecture can process clicks for multiple objects at once, and correspondingly predicts non overlapping segmentation masks without any post-processing. In the second part of this talk, I'll focus on end-to-end video segmentation networks based on 3D convolutions, and present our work STEm-Seg. STEm-Seg is a a bottom-up end-to-end approach for instance segmentation on videos, which uses a partially 3D network to learn spatio-temporal embeddings that can be clustered into instance tubes based on the predicted clustering parameters. Our method is very generic and can be applied to a wide range of instance segmentation tasks in videos. Finally, I’ll present our latest work, Point-VOS, where we show that video segmentation models can learn from spatiotemporally sparse point annotations instead of dense per-object mask annotations. We also present an efficient point-wise annotations scheme, and use it to annotate two large-scale video datasets with associated language expressions. We also present a new Point-VOS benchmark and the corresponding baselines, and show that on our point annotations can be used to achieve results close to state-of-the-art models that use dense mask supervision. Additionally, we evaluate models that connect vision and language on the VNG task, and correspondingly show that our data helps in improving their performance.

2 Monate

UnRAVeL Survey Lecture - Today!

von Kassing, Jan-Christoph

Dear all, this is a reminder for Martin Grohe's talk with the title "The Complexity of Constraint Satisfaction" taking place today (16.05) at 12:30 in the B-IT room 5053.2. Please find the details below --- Abstract --- The objective of a constraint satisfaction problem (CSP) is to assign values to variables subject to constraints on the values. Obviously, this is a very general type of problem, and it is not surprising that many algorithmic problems in various application domains can be described as CSPs. It is neither surprising that, in general, CSPs are computationally hard. Considerable efforts have been made to precisely understand the complexity of CSPs, with the goal of identifying tractable restrictions and, ultimately, determining the boundary between tractable and intractable CSPs. A deep theory based on methods from logic, combinatorics, and universal algebra has evolved around these questions. In this survey talk, I will give an overview of the main results and techniques of this theory, and I will highlight some current research topics and open questions. ---------------- Part of the programme of the research training group UnRAVeL is a series of lectures on the topics of UnRAVeL’s research thrusts algorithms and complexity, verification, logic and languages, and their application scenarios. Each lecture is given by one of the researchers involved in UnRAVeL. This years topic is "UnRAVeL - New Ideas!". In these lectures, UnRAVeL professors will discuss current research as well as highlight open problems and offer a perspective on potential future directions. All interested doctoral researchers and master students are invited to attend the UnRAVeL lecture series 2024 and engage in discussions with researchers and doctoral students. We are looking forward to seeing you at the lectures. Kind regards, Jan-Christoph for the organisation committee

2 Monate, 1 Woche

Einladung: Informatik-Oberseminar Barna Zajzon

von Abigail Morrison

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: 08.05.2024 um 09:00 Ort: Informatikzentrum, Raum 9222 in E3 Referent: Barna Zajzon, M.Sc. Lehrstuhl Informatik 3 Thema: Sequential information processing in modular spiking networks Abstract: Established paradigms formulate many cognitive processes in terms that involve the manipulation of sequentially organized time-discrete (symbolic) representations. This underscores two basic functional requirements that cortical circuits must fulfill: the ability to create suitable representations from a highly volatile and noisy environment; and the capacity to process, and learn from, their spatio-temporal structure. Combining software tools, simulation studies and theoretical analysis, this thesis entails a series of research projects with the shared goal of disentangling how modular structures enable neural circuits to learn and process sequential information in an efficient and reliable manner. The first part analyses the characteristics of state representations in modular spiking networks and the architectural and dynamical constraints that influence the system's ability to retain, transfer and integrate stimulus information in the presence of noise. It explores the novel hypothesis that modular topographic maps, a pervasive anatomical feature of the cortex, may provide a structural scaffold for sequential denoising of stimulus representations. The second part of this work is dedicated to investigating existing, biologically detailed models of sequence processing. If we are to harvest the knowledge within these models and arrive at a deeper mechanistic understanding of the involved phenomena, it is critical that the models and their findings are accessible, reproducible, and quantitatively comparable. We illustrate these aspects through a replication study and then lay the initial steps towards a conceptual and practical, theoretically-grounded framework for benchmarking and comparison of biophysical sequence learning models. Es laden ein: die Dozentinnen und Dozenten der Informatik -- Prof. Dr. Abigail Morrison Institute for Advanced SImulation (IAS-6) Jülich Research Center & Computer Science 3 - Software Engineering RWTH Aachen http://www.fz-juelich.de/inm/inm-6 http://www.se-rwth.de Office: +49 2428 8097504 Fax # : +49 2461 61-9460 Pronouns: she/her ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Jülich GmbH 52425 Jülich Sitz der Gesellschaft: Jülich Eingetragen im Handelsregister des Amtsgerichts Düren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Stefan Müller Geschäftsführung: Prof. Dr. Astrid Lambrecht (Vorsitzende), Karsten Beneke (stellv. Vorsitzender), Dr. Ir. Pieter Jansens ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

2 Monate, 3 Wochen

UnRAVeL Survey Lecture - Today!

von Kassing, Jan-Christoph

Dear all, this is a reminder for Jürgen Giesl's talk with the title "Termination and Complexity Analysis of (Probabilistic) Programs: Results and Future Work" taking place today at 12:30 in the B-IT room 5053.2. Please find the details below --- Abstract --- We give an overview on our work on developing techniques for automated termination and complexity analysis for different kinds of programs. While automated tools for the analysis of non-probabilistic programs are already very powerful, we will indicate several research problems that have to be solved in order to obtain techniques of similar power for probabilistic programs. ---------------- Part of the programme of the research training group UnRAVeL is a series of lectures on the topics of UnRAVeL’s research thrusts algorithms and complexity, verification, logic and languages, and their application scenarios. Each lecture is given by one of the researchers involved in UnRAVeL. This years topic is "UnRAVeL - New Ideas!". In these lectures, UnRAVeL professors will discuss current research as well as highlight open problems and offer a perspective on potential future directions. All interested doctoral researchers and master students are invited to attend the UnRAVeL lecture series 2024 and engage in discussions with researchers and doctoral students. We are looking forward to seeing you at the lectures. Kind regards, Jan-Christoph for the organisation committee

2 Monate, 3 Wochen

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informatik-vortraege Mai 2024