Machine Learning
In medical applications, machine learning often grapples with limited training data. Classical self-supervised deep learning techniques have been helpful in this domain, but these algorithms have yet to achieve the required accuracy for medical use. Recently quantum algorithms show promise in handling complex patterns with small datasets. To address this challenge, this study presents a novel solution that combines self-supervised learning with Variational Quantum Classifiers (VQC) and utilizes Principal Component Analysis (PCA) as the dimensionality reduction technique.
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118 Views
The dataset encompasses an extensive collection of patient information, delving into their comprehensive medical background, encompassing a myriad of features that encapsulate not only the physical but also the mental and emotional states. Furthermore, the dataset is enriched with invaluable ECG data derived from the patients. Moreover, our dataset boasts additional features meticulously extracted from the ECG records, thereby enhancing the potential for our machine learning model to undergo more effective training with our rich and diverse data.
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606 Views
The choice of the dataset is the key for OCR systems. Unfortunately, there are very few works on Telugu character datasets. The work by Pramod et al has 500 words and an average of 50 images with 50 fonts in four styles for training data each image of size 48x48 per category. They used the most frequently occurring words in Telugu but were unable to cover all the words in Telugu. Later works were based on character level. The dataset by Hastie has 460 classes and 160 samples per class which is made up of 500 images.
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681 Views
Distribution and power transformers are essential components of any electricity network, hence electrical and mechanical safety of the transformer unit is among the highest concerns of electricity providers. Over the course of their operation, transformers face with a wide range of internal and external disturbances which may lead to a partial or full malfunction of the equipment. The service life and condition requirements for distribution and power transformers are now changed and utilities altered their maintenance policy from time-based to condition-based approach.
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104 Views
We define personal risk detection as the timely identification of when someone is in the midst of a dangerous situation, for example, a health crisis or a car accident, events that may jeopardize a person’s physical integrity. We work under the hypothesis that a risk-prone situation produces sudden and significant deviations in standard physiological and behavioural user patterns. These changes can be captured by a group of sensors, such as the accelerometer, gyroscope, and heart rate.
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790 Views
Nasal cytology is a medicine field that focuses on the examination of nasal mucosa cells with the objective of recognizing changes in the epithelium, which is frequently subjected to acute or chronic irritation and inflammation caused by viruses, bacteria, or fungi; in the last decade, nasal cytology is becoming increasingly critical in diagnosing nasal conditions.
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250 Views
The Internet Graphs (IGraphs) dataset is a substantial collection of real intra-AS (Autonomous System) graphs sourced from the Internet Topology Data Kit (ITDK) project. Comprising a total of 90,326 graphs, each ranging from 12 to 250 nodes, this dataset provides a diverse and extensive resource for the exploration and analysis of network structures within autonomous systems.
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852 Views
This data set comes from the MetaFilter website. The question ID data of the askme section is obtained through the official dump data. After selecting a specific category, the corresponding other data is obtained using the ID, including the question title, description, questioner, tags, and all comments.
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28 Views
Object tracking systems within closed environments employ light detection and ranging (LiDAR) to address privacy and confidentiality. Data collection occurred in two distinct scenarios. The goal of scenario one is to detect the locations of multiple objects from various locations on a flat surface in a closed environment. The second scenario describes the effectiveness of the technique in detecting multiple objects by using LiDAR data obtained from a single, fixed location.
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423 Views
Recent advances in Wi-Fi sensing have ushered in a plethora of pervasive applications in home surveillance, remote healthcare, road safety, and home entertainment, among others. Most of the existing works are limited to the activity classification of a single human subject at a given time. Conversely, a more realistic scenario is to achieve simultaneous, multi-subject activity classification. The first key challenge in that context is that the number of classes grows exponentially with the number of subjects and activities.
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775 Views