Machine learning and deep learning: A review of methods and applications
K Sharifani, M Amini - World Information Technology and …, 2023 - papers.ssrn.com
Abstract Machine learning and deep learning have rapidly emerged as powerful tools in
many fields, including image and speech recognition, natural language processing, and …
many fields, including image and speech recognition, natural language processing, and …
A review of machine learning in processing remote sensing data for mineral exploration
The decline of the number of newly discovered mineral deposits and increase in demand for
different minerals in recent years has led exploration geologists to look for more efficient and …
different minerals in recent years has led exploration geologists to look for more efficient and …
[HTML][HTML] Deep learning in food category recognition
Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …
research for the past few decades. It is potentially one of the next steps in revolutionizing …
Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
Plant leaf detection and disease recognition using deep learning
SV Militante, BD Gerardo… - 2019 IEEE Eurasia …, 2019 - ieeexplore.ieee.org
The latest improvements in computer vision formulated through deep learning have paved
the method for how to detect and diagnose diseases in plants by using a camera to capture …
the method for how to detect and diagnose diseases in plants by using a camera to capture …
Deep learning in glaucoma with optical coherence tomography: a review
Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks,
has made significant breakthroughs in medical imaging, particularly for image classification …
has made significant breakthroughs in medical imaging, particularly for image classification …
Feature extraction by using deep learning: A survey
S Dara, P Tumma - 2018 Second international conference on …, 2018 - ieeexplore.ieee.org
Deep learning is presently an effective research area in machine learning technique and
pattern classification association. This has achieved big success in the areas of application …
pattern classification association. This has achieved big success in the areas of application …
Major depressive disorder classification based on different convolutional neural network models: deep learning approach
The human brain is characterized by complex structural, functional connections that
integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation …
integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation …
Time-frequency analysis, denoising, compression, segmentation, and classification of PCG signals
TH Chowdhury, KN Poudel, Y Hu - Ieee Access, 2020 - ieeexplore.ieee.org
Phonocardigraphy (PCG) is the graphical representation of heart sounds. The PCG signal
contains useful information about the functionality and the condition of the heart. It also …
contains useful information about the functionality and the condition of the heart. It also …
Application of deep reinforcement learning in traffic signal control: An overview and impact of open traffic data
Persistent congestions which are varying in strength and duration in the dense traffic
networks are the most prominent obstacle towards sustainable mobility. Those types of …
networks are the most prominent obstacle towards sustainable mobility. Those types of …