Machine Learning
This work presents a specialized dataset designed to advance autonomous navigation in hiking trail and off-road natural environments. The dataset comprises over 1,250 images (640x360 pixels) captured using a camera mounted on a tele-operated robot on hiking trails. Images are manually labeled into eight terrain classes: grass, rock, trail, root, structure, tree trunk, vegetation, and rough trail. The dataset is provided in its original form without augmentations or resizing, allowing end-users flexibility in preprocessing.
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The dataset provides detailed information for wheat crop monitoring in the Karnal District, India, spanning the period from 2010 to 2022. It is divided into four main components. The first component, Remote Sensing Data, includes Sentinel-2 (10 m resolution) satellite data averaged over village boundaries, specifically over a wheat crop mask. This folder contains two Excel files: one for NDVI (Normalized Difference Vegetation Index) and another for NDWI (Normalized Difference Water Index), both providing fortnightly data during the Rabi season across a 10-year period.
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This dataset, titled "Synthetic Sand Boil Dataset for Levee Monitoring: Generated Using DreamBooth Diffusion Models," provides a comprehensive collection of synthetic images designed to facilitate the study and development of semantic segmentation models for sand boil detection in levee systems. Sand boils, a critical factor in levee integrity, pose significant risks during floods, necessitating accurate and efficient monitoring solutions.
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234 Views
We organized and collected two years' worth of complete fault work orders from a wind farm, and structured these work orders into a fault diagnosis event knowledge graph using the proposed algorithm. This graph includes fault modes, fault impacts, fault symptoms, inspection schemes, root cause identification, and maintenance strategies, covering all potential fault information and handling methods for wind turbines. This dataset records the head entity-relation-tail entity information in the form of triples using JSON format.
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340 Views
This dataset presents real-world VPN encrypted traffic flows captured from five applications that belong to four service categories, which reflect typical usage patterns encountered by everyday users.
Our methodology utilized a set of automatic scripts to simulate real-world user interactions for these applications, to achieve a low level of noise and irrelevant network traffic.
The dataset consists of flow data collected from four service categories:
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85 Views
To download the dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13738598
Please cite the following paper when using this dataset:
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328 Views
Resource usage fuzzing samples and related data. Contains samples from Pythoin, random data, GPT-3.5, GPT-4, Gemini-1.0, Claude Instant, and Claude Opus. These samples are generated for 50 Python functions. Also included are resource measures for CPU time, instruction count, function calls, peak RAM usage, final RAM allocated, and coverage. These values were collected on an isolated system and account for interference from other processes.
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54 Views
The limited availability of Guitar notes datasets hinders the training of any artificial intelligence model in this field. TaptoTab dataset aims to fill this gap by providing a collection of notes recordings. This dataset is collected as part of an honours project at the Faculty of Computer and Information Sciences, Ain Shams University. The dataset is composed of audio data that has been self-collected, focusing on capturing a comprehensive range of guitar notes. The dataset consists of recordings of guitar notes played on each of the six strings, covering up to the 12th fret.
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455 Views
The data in this dataset is the experimental data related to the article named Privacy-preserving approach to edge federated learning based on blockchain and fully homomorphic encryption , which contains data such as running time comparison, communication spend comparison, encryption and decryption time comparison, accuracy comparison, etc.
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39 Views
Brain-Computer Interface (BCI) technology facilitates a direct connection between the brain and external devices by interpreting neural signals. It is critical to have datasets that contain patient's native languages while developing BCI-based solutions for neurological disorders. However, present BCI research lacks appropriate language-specific datasets, particularly for languages such as Telugu, which is spoken by more than 90 million people in India.
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253 Views