classification

This dataset contains RF signals from drone remote controllers (RCs) of different makes and models. The RF signals transmitted by the drone RCs to communicate with the drones are intercepted and recorded by a passive RF surveillance system, which consists of a high-frequency oscilloscope, directional grid antenna, and low-noise power amplifier. The drones were idle during the data capture process. All the drone RCs transmit signals in the 2.4 GHz band. There are 17 drone RCs from eight different manufacturers and ~1000 RF signals per drone RC, each spanning a duration of 0.25 ms. 

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Morse code is a system of communication using dots and dashes to represent numbers, letters and symbols. For example, the letter 'B' is represented as a dash followed by 3 dots, i.e. "–...". The dataset used in this competition is synthetically generated, and mimics a human writing dots and dashes on a piece of paper. In this sense, it is like a 1-dimensional version of an image represented by numeric pixel values. The challenge is to classify the resulting 1-dimensional input into 1 out of 64 classes which represent various letter, numbers and symbols.

Last Updated On: 
Tue, 07/14/2020 - 21:14

The dataset comprises of image file s of size 20 x 20 pixels for various types of metals and non-metal.The data collected has been augmented, scaled and modified to represent a number a training set dataset.It can be used to detect and identify object type based on material type in the image.In this process both training data set and test data set can be generated from these image files. 

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1932 Views

We introduce a novel dataset containing a total of 61 distinct HEAs. The proposed appliances (e.g. fans, fridges, washers, etc.) are of different kinds, ages, brands and power
levels. They have been recorded in steady-state conditions in a French 50 Hz electrical grid. The measurement setup consists of an AC current probe (E3N Chauvin Arnoux) with a 10 mV/A sensitivity and a differential voltage probe with

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1393 Views

CUPSNBOTTLES is an object data set, recorded by a mobile service robot. There are 10 object classes, each with a varying number of samples. Additionally, there is a clutter class, containing samples where the object detector failed.

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475 Views

The development of electronic nose (e-nose) for a rapid, simple, and low-cost meat assessment system becomes the concern of researchers in recent years. Hence, we provide time-series datasets that were recorded from e-nose for beef quality monitoring experiment. This dataset is originated from 12 type of beef cuts including round (shank), top sirloin, tenderloin, flap meat (flank), striploin (shortloin), brisket, clod/chuck, skirt meat (plate), inside/outside, rib eye, shin, and fat.

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1563 Views

This dataset comes up as a benchmark dataset for machines to automatically recognizing the handwritten assamese digists (numerals) by extracting useful features by analyzing the structure. The Assamese language comprises of a total of 10 digits from 0 to 9. We have collected a total of 516 handwritten digits from 52 native assamese people irrespective of their age (12-86 years), gender, educational background etc. The digits are captured in .jpeg format using a paint mobile application developed by us which automatically saves the images in the internal storage of the mobile.

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1129 Views

The recent interest in using deep learning for seismic interpretation tasks, such as facies classification, has been facing a significant obstacle, namely the absence of large publicly available annotated datasets for training and testing models. As a result, researchers have often resorted to annotating their own training and testing data. However, different researchers may annotate different classes, or use different train and test splits.

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1551 Views

Network traffic analysis, i.e. the umbrella of procedures for distilling information from network traffic, represents the enabler for highly-valuable profiling information, other than being the workhorse for several key network management tasks. While it is currently being revolutionized in its nature by the rising share of traffic generated by mobile and hand-held devices, existing design solutions are mainly evaluated on private traffic traces, and only a few public datasets are available, thus clearly limiting repeatability and further advances on the topic.

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1875 Views

We present two synthetic datasets on classification of Morse code symbols for supervised machine learning problems, in particular, neural networks. The linked Github page has algorithms for generating a family of such datasets of varying difficulty. The datasets are spatially one-dimensional and have a small number of input features, leading to high density of input information content. This makes them particularly challenging when implementing network complexity reduction methods.

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657 Views

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