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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,673 datasets
A historical and political analysis titled 'Islam in China. A neglected problem' authored by Marshall Broomhall. The dataset likely contains textual content related to the study of Islam within China. It is published on the paperswithcode platform.
A text collection titled 'America and the Islamic Bomb: The Deadly Compromise' by David Armstrong, published on the paperswithcode platform. The dataset likely contains historical and political analysis concerning nuclear weapons, Islam, and international compromise. The specific content, size, and update date are unknown.
Anna Mansson McGinty authored a study on Western women converting to Islam. The dataset likely contains qualitative research data, such as interviews or narratives, related to religious conversion and identity. It is published on paperswithcode, a platform for academic papers with associated code.
A dataset from paperswithcode by author Michael C. Dreiling. It likely contains textual or tabular data related to the political economy of the NAFTA trade agreement, focusing on security and sustainability conflicts. The specific temporal coverage, row count, and file formats are unknown.
Edward Mortimer authored a work on the intersection of Islam, faith, and political power. The dataset likely contains textual content related to political science and religious studies. It is published on the paperswithcode platform.
A multimodal dataset designed for autonomous driving applications, focusing on two-wheeler vehicles. The dataset likely contains sensor data relevant to vehicle navigation and control. The preview version is hosted on Kaggle.
A dataset titled 'conservation_drones_real' is hosted on Kaggle. The dataset likely contains data collected by drones for environmental conservation purposes. Metadata is minimal; the specific content, scale, and origin require verification after download.
DisasterM3 is a remote sensing vision-language dataset for disaster damage assessment and response. It contains 26,988 bi-temporal satellite images and 123,000 instruction-response pairs. The dataset was created by researchers including Junjue Wang and Weihao Xuan, with a paper published in 2025.
A multimodal benchmark designed to evaluate Multimodal Large Language Models (MLLMs) in low-altitude UAV scenarios. It contains 19 tasks across three capability dimensions: perception, cognition, and planning. The dataset was created by author 'daisq' and was last updated on January 18, —.
This replication package provides the data used by Duncan Webb for the study 'Silence to Solidarity,' published in the Journal of Political Economy. Updated in March 2026, the collection facilitates the analysis of how communication patterns influence discriminatory behavior toward minorities. It serves as the primary evidence base for social science research into communication and social interactions.
KITTI is a widely recognized benchmark dataset for autonomous driving research. The dataset likely contains sensor data annotations, such as bounding boxes for objects in traffic scenes. It is published on Kaggle, but specific details about its size, columns, and version are unknown.
UAV Tracking Frames Final is a dataset hosted on Kaggle. Its title suggests it likely contains video frames or sequences related to tracking Unmanned Aerial Vehicles. The dataset's specific content, size, and origin are unknown from the provided metadata.
Drone imagery likely collected for forest fire monitoring missions. The dataset is hosted on Kaggle, but specific details about its size, collection dates, and authorship are unknown. Its content appears to focus on aerial observations of fire events.
Cornea-external-uav is a dataset hosted on Kaggle. The title suggests it contains imagery of the external cornea, likely captured using unmanned aerial vehicle (UAV) technology. The dataset's specific contents, scale, and origin require verification after download.
UIT-ADrone is a dataset of aerial imagery collected by drones, published on Kaggle. The dataset's specific content, scale, and creation details are not provided in the available metadata. Further details such as the number of images, annotation types, and collection timeframe require verification after download.
Collision data from Waymo's autonomous vehicle operations in 2025. The dataset is hosted on Kaggle, but its specific scope, size, and collection methodology are not detailed in the provided metadata. Further verification is required to confirm the exact content and structure.
GLDD provides labeled imagery for identifying diseases affecting guava plants. The dataset's size, creator, and update date are unspecified. It is intended for applications in AI-driven precision agriculture.
GLDD provides labeled images of guava leaves for disease classification tasks in precision agriculture. The dataset's size, creator, and update date are not specified in the provided information.
LejuRobotics released this industrial dataset for the 1st Real-World Embodied-AI Learning Challenge (REAL-I) at ICRA 2026. It consists of approximately 1,000 image records captured from both simulated and real-world robotic platforms.
Drone Detection Premium is a dataset hosted on Kaggle. Its title and platform tags suggest it contains imagery for detecting drones, likely in aerial or ground-based contexts. The dataset's specific size, source, and creation details are not provided in the available metadata.