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 original data, this data set only contains a part of road images. If you feel it is useful for your research, please email (wangzhangu1@163.com) to get the complete data set.
- Categories:
453 Views
The dataset file contains all the relevant data for this paper, including original text data, labels, and statistical information, which is utilized for training, testing, and validation of the proposed models or arguments. Additionally, there is a question bank file that comprises all test questions, filtered test data, and annotated result data after testing. This data is used to evaluate the performance of the models or methods proposed in the paper.
- Categories:
373 Views
The dataset file contains all the relevant data for this paper, including original text data, labels, and statistical information, which is utilized for training, testing, and validation of the proposed models or arguments. Additionally, there is a question bank file that comprises all test questions, filtered test data, and annotated result data after testing. This data is used to evaluate the performance of the models or methods proposed in the paper.
- Categories:
Views
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.
- Categories:
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.
- Categories:
737 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.
- Categories:
448 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.
- Categories:
527 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.
- Categories:
2582 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
- Categories:
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.
- Categories:
673 Views