Machine Learning

Tactile perception of the material properties in real-time using tiny embedded systems is a challenging task and of grave importance for dexterous object manipulation such as robotics, prosthetics and augmented reality [1-4] . As the psychophysical dimensions of the material properties cover a wide range of percepts, embedded tactile perception systems require efficient signal feature extraction and classification techniques to process signals collected by tactile sensors in real-time.

110 views
  • Machine Learning
  • Last Updated On: 
    Mon, 03/30/2020 - 16:05

    Conveyor belts are the most widespread means of transportation for large quantities of materials in the mining sector. This dataset contains 388 images of structures with and without dirt buildup.

    One can use this dataset for experimentation on classifying the dirt buildup.

    71 views
  • Artificial Intelligence
  • Last Updated On: 
    Wed, 01/29/2020 - 18:54

    This dataset covers cellular communication signals in the SCF format. There is a total of 60000 signal instances, 36000 of them are reserved as training data and the rest is for the test. The SNR levels are between 1 dB and 15 dB.

    84 views
  • Machine Learning
  • Last Updated On: 
    Mon, 01/20/2020 - 15:16

    The 2020 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) and the Technical University of Munich, aims to promote research in large-scale land cover mapping based on weakly supervised learning from globally available multimodal satellite data. The task is to train a machine learning model for global land cover mapping based on weakly annotated samples.

  • Artificial Intelligence
  • Machine Learning
  • Image Fusion
  • Geoscience and Remote Sensing
  • Last Updated On: 
    Fri, 03/06/2020 - 07:28

    Dataset for Telugu Handwritten Gunintam

    179 views
  • Computer Vision
  • Last Updated On: 
    Fri, 11/29/2019 - 07:25

    This dataset is part of my PhD research on malware detection and classification using Deep Learning. It contains static analysis data: Top-1000 imported functions extracted from the 'pe_imports' elements of Cuckoo Sandbox reports. PE malware examples were downloaded from virusshare.com. PE goodware examples were downloaded from portableapps.com and from Windows 7 x86 directories.

    552 views
  • Machine Learning
  • Last Updated On: 
    Fri, 11/08/2019 - 05:43

    This dataset is part of my PhD research on malware detection and classification using Deep Learning. It contains static analysis data: Raw PE byte stream rescaled to a 32 x 32 greyscale image using the Nearest Neighbor Interpolation algorithm and then flattened to a 1024 bytes vector. PE malware examples were downloaded from virusshare.com. PE goodware examples were downloaded from portableapps.com and from Windows 7 x86 directories.

    195 views
  • Machine Learning
  • Last Updated On: 
    Thu, 11/07/2019 - 11:45

    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.

    270 views
  • Computer Vision
  • Last Updated On: 
    Wed, 11/06/2019 - 04:14

    This dataset is part of my PhD research on malware detection and classification using Deep Learning. It contains static analysis data (PE Section Headers of the .text, .code and CODE sections) extracted from the 'pe_sections' elements of Cuckoo Sandbox reports. PE malware examples were downloaded from virusshare.com. PE goodware examples were downloaded from portableapps.com and from Windows 7 x86 directories.

    439 views
  • Machine Learning
  • Last Updated On: 
    Wed, 11/06/2019 - 06:10

    An accurate and reliable image-based quantification system for blueberries may be useful for the automation of harvest management. It may also serve as the basis for controlling robotic harvesting systems. Quantification of blueberries from images is a challenging task due to occlusions, differences in size, illumination conditions and the irregular amount of blueberries that can be present in an image. This paper proposes the quantification per image and per batch of blueberries in the wild, using high definition images captured using a mobile device.

    800 views
  • Artificial Intelligence
  • Last Updated On: 
    Thu, 01/02/2020 - 09:36

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