AIMC Topic: Data Collection

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Weather Classification by Utilizing Synthetic Data.

Sensors (Basel, Switzerland) Apr 21, 2022
Weather prediction from real-world images can be termed a complex task when targeting classification using neural networks. Moreover, the number of images throughout the available datasets can contain a huge amount of variance when comparing location...
Neural Networks, Computer Weather Data Collection Vision, Ocular
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Deep learning-enabled mobile application for efficient and robust herb image recognition.

Scientific reports Apr 21, 2022
With the increasing popularity of herbal medicine, high standards of the high quality control of herbs becomes a necessity, with the herb recognition as one of the great challenges. Due to the complicated processing procedure of the herbs, methods of...
Deep Learning Smartphone Mobile Applications Data Collection Phytotherapy
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Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Apr 16, 2022
Autonomous systems are becoming ubiquitous and gaining momentum within the marine sector. Since the electrification of transport is happening simultaneously, autonomous marine vessels can reduce environmental impact, lower costs, and increase efficie...
Humans Machine Learning Data Collection Reinforcement, Psychology
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Deep Learning Approach to UAV Detection and Classification by Using Compressively Sensed RF Signal.

Sensors (Basel, Switzerland) Apr 16, 2022
Recently, the frequent occurrence of the misuse and intrusion of UAVs has made it a research challenge to identify and detect them effectively, and relatively high bandwidth and pressure on data transmission and real-time processing exist when sampli...
Neural Networks, Computer Algorithms Research Design Deep Learning Data Collection
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Cross subkey side channel analysis based on small samples.

Scientific reports Apr 15, 2022
The majority of recently demonstrated Deep-Learning Side-Channel Analysis (DLSCA) use neural networks trained on a segment of traces containing operations only related to the target subkey. However, when the size of the training set is limited, as in...
Neural Networks, Computer Research Design Deep Learning Data Collection Food, Formulated
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WalkIm: Compact image-based encoding for high-performance classification of biological sequences using simple tuning-free CNNs.

PloS one Apr 15, 2022
The classification of biological sequences is an open issue for a variety of data sets, such as viral and metagenomics sequences. Therefore, many studies utilize neural network tools, as the well-known methods in this field, and focus on designing cu...
Neural Networks, Computer Research Design Data Collection Metagenomics
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DeepLumina: A Method Based on Deep Features and Luminance Information for Color Texture Classification.

Computational intelligence and neuroscience Apr 14, 2022
Color texture classification is a significant computer vision task to identify and categorize textures that we often observe in natural visual scenes in the real world. Without color and texture, it remains a tedious task to identify and recognize ob...
Neural Networks, Computer Research Design Support Vector Machine Color Data Collection
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Sensor Fault Diagnosis Using a Machine Fuzzy Lyapunov-Based Computed Ratio Algorithm.

Sensors (Basel, Switzerland) Apr 13, 2022
Anomaly identification for internal combustion engine (ICE) sensors has become an important research area in recent years. In this work, a proposed indirect fuzzy Lyapunov-based computed ratio observer integrated with a support vector machine (SVM) w...
Algorithms Feedback Support Vector Machine Fuzzy Logic Data Collection
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Practical foundations of machine learning for addiction research. Part II. Workflow and use cases.

The American journal of drug and alcohol abuse Apr 7, 2022
In a continuum with applied statistics, machine learning offers a wide variety of tools to explore, analyze, and understand addiction data. These tools include algorithms that can leverage useful information from data to build models; these models ca...
Humans Machine Learning Workflow Data Collection
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Zero-Day Malware Detection and Effective Malware Analysis Using Shapley Ensemble Boosting and Bagging Approach.

Sensors (Basel, Switzerland) Apr 6, 2022
Software products from all vendors have vulnerabilities that can cause a security concern. Malware is used as a prime exploitation tool to exploit these vulnerabilities. Machine learning (ML) methods are efficient in detecting malware and are state-o...
Machine Learning Software Algorithms Data Collection Computer Security
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