Titlebook: Intelligent Systems and Applications; Proceedings of the 2 Kohei Arai Conference proceedings 2024 The Editor(s) (if applicable) and The Aut

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ASR Bundestag: A Large-Scale Political Debate Dataset in German,raining as well as 1,038 h of unlabeled audio snippets for self-supervised learning, based on raw audio data and transcriptions from plenary sessions and committee meetings of the German parliament. In addition, we discuss utilized approaches for the automated creation of speech datasets and assess

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,Prototype App Mobile for Real Time American Sign Language Recognition Based on Deep Learning,hm has demonstrated a very high learning rate. Other researchers have created and published a dataset consisting of approximately 200 images of static gestures of the American Sign Language alphabet. For this research work, the aforementioned dataset was used, and the gestures were captured and trai

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A Novel DNN-Based IDS System Combined with an LR-GA Method to Detect Attacks,ing more complicated and harder to spot. Hence, many intelligent attack detection approaches have been developed to face these problems in recent years. Intrusion detection systems (IDSs) based on machine learning approaches have been rising strongly due to their efficiency and scalability. However,

Laconic

,Identification of Potato Virus Y in Potato Plants Using Deep Learning and GradCAM Verification,ntly use manual visual inspections to classify potato plants that are diseased with the potato virus Y. This paper shows the feasibility of using RGB images to automate this process. A small dataset of potato plants pictures was acquired from an outdoor potato field and annotated with polygons to de

Mortal

,Using Simulated Data for Deep-Learning Based Real-World Apple Detection,s involves acquiring numerous images and manually annotating them. In this paper, we introduce a method for simulating apple orchards utilizing the Unity 3D engine. We created a tool that uses this simulator to generate fully bounding-box annotated (simulated) datasets. We trained YOLOv5 models of d

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Attention-Based Recurrent Neural Network for Multicriteria Recommendations,sufficient information about the reasons that led to a user‘s overall rating. Therefore, multicriteria recommender systems have been developed to benefit from user preferences expressed across variety of criteria. Recurrent neural networks (RNNs) have been also used in recommendation systems; indeed

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https://doi.org/10.1007/978-3-8349-8248-3Design; Geschmacksmusterrecht; IP-Rechte; Intellectual Property; Kommunikation; Konkursordnung; Marke; Mark

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