Machine Learning
The existing datasets lack the diversity required to train the model so that it performs equally well in real fields under varying environmental conditions. To address this limitation, we propose to collect a small number of in-field data and use the GAN to generate synthetic data for training the deep learning network. To demonstrate the proposed method, a maize dataset 'IIITDMJ_Maize' was collected using a drone camera under different weather conditions, including both sunny and cloudy days. The recorded video was processed to sample image frames that were later resized to 224 x 224.
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366 Views
this is a dataset for Human-Robot Physical Contact Classification. We used the UR10e six-axis robotic arm as the data collection object and the official tool, RTDE, as the data acquisition tool. Regarding the labels of the dataset, we categorize Human-Robot physical contact into three types: no contact, intentional contact, and collision, based on common occurrences in Human-Robot collaborative tasks. The dataset contains 2375 non-repetitive data entries with valid Human-Robot physical contact information, and each entry includes the motion data of the robotic arm within 1 second.
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167 Views
The SaudiShopInsights dataset is a comprehensive collection of customer reviews in the Arabic language, specifically focusing on the Saudi dialect, within the domains of fashion and electronics. Gathered from various online platforms, this dataset serves as a valuable resource for researchers and practitioners interested in sentiment analysis, natural language processing, and customer behavior studies.
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375 Views
The dataset comprises diverse objects detectable by drones during aerial surveys, encapsulating an extensive array of environmental and man-made elements. Encompassing natural entities like trees, water bodies, terrain features, and vegetation, it also incorporates urban objects such as buildings, roads, vehicles, and infrastructure. The dataset delineates distinct categories, encompassing fine-grained details within each classification, catering to the nuances of aerial detection.
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186 Views
The provided dataset appears to contain weather-related information for New Delhi Safdarjung, India, spanning from January 1, 2023, to July 21, 2023. The dataset includes the following columns: Station ID, Station Name, Date, Precipitation (PRCP), Average Temperature (TAVG), Maximum Temperature (TMThe dataset includes daily observations with information on precipitation and temperature. It seems that some values are missing (NULL values), and there are variations in the units used for precipitation AX), and Minimum Temperature (TMIN).
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2108 Views
The Wind Power Technology Dataset is a comprehensive collection of data related to wind energy generation technology. This dataset encompasses a wide range of information, including meteorological data, turbine specifications, power output records, and environmental factors. It provides a valuable resource for researchers, engineers, and stakeholders in the renewable energy sector.
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3502 Views
With the widespread use of the Portable Document Format (PDF), it’s increasingly becoming a target for malware, highlighting the need for effective detection solutions. In recent years, machine learning-based methods for PDF malware detection have grown in popularity. However, the effectiveness of ML models is closely related to the quality of the training datasets. In this research, we investigated two widely used PDF malware datasets: Contagio and CIC. We found biases and representativeness issues that could affect the reliability and applicability of models built on them.
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392 Views
Volkswagen Group of America Innovation and Engineering Center California (VW IECC) is a research facility in Belmont, California working on the future of the mobility. In the recent years exciting developments have happened for the autonomous vehicles. In general, lack of data is the main problem to tackle to solve the task of autonomous driving. One of the important tasks in this topic is the overtaking and lane changes, especially in the highway scenarios.
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343 Views
In the contemporary cybersecurity landscape, robust attack detection mechanisms are important for organizations. However, the current state of research in Software-Defined Networking (SDN) suffers from a notable lack of recent SDN-OpenFlow-based datasets. Here we introduce a novel dataset for intrusion detection in Software-Defined Networking named SDNFlow. The dataset, derived from OpenFlow statistics gathered from real traffic, integrates a comprehensive range of network activities.
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1265 Views
Accurate knowledge of key genes that promote hair follicle growth and development is of great value in the field of hair research and dermatology. Compared with the traditional time-consuming and laborious experimental methods for obtaining key genes, the literature mining method can extract proven key genes for hair follicle growth from the vast amount of literature more quickly and comprehensively, i.e., perform the tasks of Named Entity Recognition (NER) and Relationship Extraction (RE) of related entities.
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95 Views