Artificial Intelligence
This data set contains four types of road images: asphalt roads and gravel roads; Wading roads and snowy roads. It is mainly used to train road recognition models. Due to the large amount of data, this data set only contains some images. If you feel it is useful for your research, please email wangzhangu1@163.com to get the complete data set.
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46 Views
Seven years of water consumption data, along with population data, were manually collected in collaboration with the local municipality office. This data was then combined with climatic data to model the proposed machine learning algorithm. The weather data was recorded for a period of 7 years using precise meteorological instruments installed in Islamabad at coordinates 33.64° N and 72.98° E, with an elevation of 500 meters above sea level.
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739 Views
We present the RQMD dataset, a comprehensive collection of diverse material samples aimed at advancing computer vision and machine learning algorithms in terrain classification tasks. This dataset contains RGB images of 5 different terrains, such as Asphalt, Brick, Grass, Gravel, and Tiles, captured using an 8-megapixel Raspberry Pi camera from a top-view perspective. Notably, the dataset encompasses images taken at different times of the day, introducing variations in lighting conditions and environmental factors.
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449 Views
Lettuce Farm SLAM Dataset (LFSD) is a VSLAM dataset based on RGB and depth images captured by VegeBot robot in a lettuce farm. The dataset consists of RGB and depth images, IMU, and RTK-GPS sensor data. Detection and tracking of lettuce plants on images are annotated with the standard Multiple Object Tracking (MOT) format. It aims to accelerate the development of algorithms for localization and mapping in the agricultural field, and crop detection and tracking.
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528 Views
The demand for artificial intelligence (AI) in healthcare is rapidly increasing. However, significant challenges arise from data scarcity and privacy concerns, particularly in medical imaging. While existing generative models have achieved success in image synthesis and image-to-image translation tasks, there remains a gap in the generation of 3D semantic medical images. To address this gap, we introduce Med-DDPM, a diffusion model specifically designed for semantic 3D medical image synthesis, effectively tackling data scarcity and privacy issues.
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2589 Views
This dataset contains image masks from KiTTy obtained by running SAM. In the future, it is planned to add other masks from OpenSEED, SEEM, SAM (new version).
The study is carried out in order to study segmentation on point clouds
This dataset contains image masks from KiTTy obtained by running SAM. In the future, it is planned to add other masks from OpenSEED, SEEM, SAM (new version).
The study is carried out in order to study segmentation on point clouds
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139 Views
Surveillance videos taken in unconstrained environments can be tampered with due to different environmental factors and malicious human activities. They often blur the video content and introduce difficulty in identifying the events in the scene. The problem is particularly acute for smart surveillance systems that need to make real-time decisions based on the video. Automatic detection of the blur anomalies in the video is crucial to these systems. In this research, a learning-based approach for camera blur detection is proposed.
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674 Views
The focus has been on investors’ hopes for the stock market for a considerable amount of time.Becauseoftheanticipatedhighreturns,thisisthepreferredinvestmentoption.However,dueto the significance of accurate forecasting, such investments are high-risk. In order to analyze stock market forecasts, investors utilize a technical analyst and AI technologies.
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17 Views
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354 Views
This study proposes a more competitive and sample-efficient algorithm: Memory-GIC-PPO, specifically to address POMDPs in UAV path planning. The effectiveness of the proposed algorithm is thoroughly evaluated through simulations conducted on the Airsim platform. The results convincingly demonstrate that Memory-GIC-PPO enables the UAV to achieve optimal path planning in complex environments and outperforms the benchmark algorithms in terms of sampling efficiency and success rates.
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304 Views