Artificial Intelligence
We release MarsScapes, the first panorama dataset for Martian terrain understanding. The dataset contains 195 panoramas of Mars surface with fine-grained annotations for semantic and instance segmentation, facilitating high-level scene understanding of Martian landforms and further enhancing the navigability of rovers over rough terrains in large areas. Note: Limited by the file size, we temporarily submit the first half of MarsScapes (i.e. from 122_1 to 527_1) as a representative subset. All samples will be provided after our paper is accepted.
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Deep learning has revolutionized the field of robotics. To deal with the lack of annotated training samples for learning deep models in robotics, Sim-to-Real transfer has been invented and widely used. However, such deep models trained in simulation environment typically do not transfer very well to the real world due to the challenging problem of “reality gap”. In response, this letter presents a conceptually new Digital Twin (DT)-CycleGAN framework by integrating the advantages of both DT methodology and the CycleGAN model so that the reality gap can be effectively bridged.
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Chat GPT Prompt:
Create a CSV file with 10000 rows of weather data from the fictions town named Anytown. Please include temperature, barometer readings, wind speed, wind direction, precipitation, dew point, humidity, and conditions.
Response:
Here's a sample CSV file with 10000 rows of weather data for Anytown. This data is randomly generated for demonstration purposes only, so it does not represent actual weather conditions.
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The dataset contains pressure insole data from twenty subjects who performed five tasks, comprising of two common daily activities (standing and walking), and three industry-focussed tasks (manual handling, assembly and pick and place). The speed and order in which a given task was completed was not prescribed. The data pertains to the areas of human factors, ergonomics and occupational health and safety research, among others, and enables an understanding of the force distributions involved in common tasks as well as physical and manufacturing type tasks.
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Most of the existing human action datasets are common human actions in daily scenes(e.g. NTU RGB+D series, Kinetics series), not created for Human-Robot Interaction(HRI), and most of them are not collected based on the perspective of the service robot, which can not meet the needs of vision-based interactive action recognition.
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The dataset includes channel frequency response (CFR) data collected through an IEEE 802.11ax device for human activity recognition. This is the first dataset for Wi-Fi sensing with the IEEE 802.11ax standard which is the most updated Wi-Fi version available in commercial devices. The dataset has been collected within a single environment considering a single person as the purpose of the study was to evaluate the impact of communication parameters on the performance of sensing algorithms.
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The rocket nose-cone shapes have been generated by blending few conic sections together (two conic sections in one) and the simulated against mach number regime from subsonic through transonic to supersonic. The aerodynamic drag coefficients have been recoded for each shape for each mach number.
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Open set face recognition on a small dataset, in terms of the amount of image samples per individual, is a hard and active area of study. This study investigates the open set face verification and face identification problems on the IFPLD dataset, which consists of only one frontal and one profile image per individual.
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This dataset contains trained weights to predict ECG abnormalities.
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This folder consists of codes, dataset, and models.
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