Fraunhofer IMTE · IMTE - Einrichtung für Individualisierte Medizintechnik

Student / Thesis

Studentische Hilfskraft - Frontend-Entwicklung & UX-Design für Medizintechnik (all genders)

BEI UNS DREHT SICH ALLES UM DIE GESUNDHEIT – UND UNSERE MITARBEITENDEN. VERÄNDERUNG STARTET MIT UNS. Haben Sie Interesse an innovativer Medizintechnik? Bei der Fraunhofer-Einrichtung für Individualisierte Medizintechnik IMTE entwickeln wir Medizinprodukte für Diagnose- und Therapieanwendungen. Durch unsere offene, diverse und inklusive Forschungskultur fördern wir Innovationen, indem wir unterschiedliche Perspektiven und Erfahrungen einbeziehen. Wir bieten ein einzigartiges Leistungsportfolio für die Medizinprodukteindustrie und decken den gesamten Entwicklungsprozess ab – von der…

🇩🇪 Lübeck

No deadlineSource: Fraunhofer IMTE

Fraunhofer IMTE · IMTE - Einrichtung für Individualisierte Medizintechnik

Student / Thesis

Masterarbeit: Echtzeit-Stresserkennung (all genders)

Das Fraunhofer IMTE bietet eine Masterarbeit in der Abteilung Rehabilitation mit der Thematik: Entwicklung und Validierung eines tragbaren Systems zur Echtzeit-Stresserkennung Ziel dieses Projekts ist die Entwicklung eines tragbaren Geräts zur Echtzeit-Erkennung von Stress unter Verwendung eines bestehenden, vortrainierten Modells für maschinelles Lernen. Das Ausgangsmodell wird zu Beginn des Projekts bereitgestellt. Dieses Projekt soll auf einer Methode zur Stresserkennung basieren, die auf IMU-Sensordaten beruht. Was Sie bei uns tun Im Rahmen dieser Forschungsarbeit sind zwei…

🇩🇪 Lübeck

No deadlineSource: Fraunhofer IMTE

Fraunhofer SIT · SIT - Secure Information Technology

Student / Thesis

Master's Thesis: Explainability of Transformer Models in Authorship Verification

Background/Motivation: Authorship verification (AV) is used in areas such as forensics, plagiarism detection, and fake news detection to identify the true author of a text. The goal of authorship verification (AV) is to classify whether two or more texts were written by the same author (Y) or not (N). As in most AI fields today, the most powerful models are usually based on transformer architectures. While these continuously achieve new state-of-the-art results, the application of explainability methods is mostly limited to somewhat older models or architectures. This limits the applicability…

🇩🇪 Darmstadt

No deadlineSource: Fraunhofer SIT

Fraunhofer SIT · SIT - Secure Information Technology

Student / Thesis

Master's Thesis: Detection of Suggestive Poses and Facial Expressions

Background/Motivation: For the detection of erotic and pornographic images, models that can recognise human skin, body parts, or scenes are often used. With the help of appropriate datasets [1], classification and object detection models can be trained. However, there are also images that are obviously erotic or pornographic, but cannot be recognised by conventional methods. This applies, for example, to images in which erotic poses or partial sections of pornographic scenes can be recognised. Here, poses and facial expressions can be used for classification, among other things [2].…

🇩🇪 Darmstadt

No deadlineSource: Fraunhofer SIT

Fraunhofer SIT · SIT - Secure Information Technology

Student / Thesis

Master's Thesis: Detection and Segmentation of Suggestive Clothing

Background/Motivation: Models that can recognise human skin, body parts, or scenes are often used to detect erotic and pornographic material. With the help of appropriate datasets [1], classification and object detection models can be trained. However, there are also images that are obviously erotic or pornographic, but cannot be recognised by conventional methods. This applies, for example, to people in skin-tight latex or leather clothing. Existing approaches in the field of "Human Parsing" can already segment people and their clothing well. Additionally, datasets like Fashionpedia [2]…

🇩🇪 Darmstadt

No deadlineSource: Fraunhofer SIT

Fraunhofer SIT · SIT - Secure Information Technology

Student / Thesis

Master's Thesis: Attacking Current Backdoor Detection Methods

Background/Motivation: Backdoor attacks are attacks on neural networks where a so-called trigger alters the decision-making behaviour of the networks, thereby creating vulnerabilities. These triggers can be injected into the training dataset or directly into the model weights. These are then called poisoned. Due to parameter-efficient fine-tuning methods, backdoor attacks on large language models (LLMs) have become significantly more difficult to detect, as a poisoned parameter update is harder to recognise than a poisoned dataset. Therefore, several methods have been developed recently to…

🇩🇪 Darmstadt

No deadlineSource: Fraunhofer SIT

Master's Thesis: 3D Modeling and Print Data Generation (all genders)

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Studentische Hilfskraft - Frontend-Entwicklung & UX-Design für Medizintechnik (all genders)

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