A survey of deep learning and its applications: a new paradigm to machine learning
… Deep learning paradigm uses a massive ground truth designated data to find the unique
features, combinations of features and then constructs an integrated feature extraction and …
features, combinations of features and then constructs an integrated feature extraction and …
The learning paradigm
J Tagg - Bolton. Anker, 2003 - api.taylorfrancis.com
… to create deep learning environments. In this chapter, I will analyze the main characteristics
of the Learning paradigm, … every aspect of the deep learning process in our own classrooms. …
of the Learning paradigm, … every aspect of the deep learning process in our own classrooms. …
Exploiting the deep learning paradigm for recognizing human actions
… In this paper we propose a novel strategy based on deep learning: differently from other
methods, a first level feature vector is extracted by using a set of features derived from depth …
methods, a first level feature vector is extracted by using a set of features derived from depth …
Face segmentation: A journey from classical to deep learning paradigm, approaches, trends, and directions
… in SOA approaches based on the deep learning architecture. A comparison of the previous
… the shift in SOA towards the new paradigm of the deep learning architecture. The rest of the …
… the shift in SOA towards the new paradigm of the deep learning architecture. The rest of the …
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Symtosis: A liver ultrasound tissue characterization and risk stratification in optimized deep learning paradigm
… , this study presents a Deep Learning (DL)-based paradigm that computes nearly seven …
the cross-validation (training and testing) paradigm. The DL architecture consists of cascaded …
the cross-validation (training and testing) paradigm. The DL architecture consists of cascaded …
[HTML][HTML] Integrated deep learning paradigm for document-based sentiment analysis
P Atandoh, F Zhang, D Adu-Gyamfi, PH Atandoh… - Journal of King Saud …, 2023 - Elsevier
… The most recent breakthroughs in deep learning for text classification often center on …
Here we look at how lexicons, machine learning, and deep learning may all be used to better …
Here we look at how lexicons, machine learning, and deep learning may all be used to better …
Deep learning for wireless communications: An emerging interdisciplinary paradigm
… The amazing success of deep learning in various fields, particularly in computer science,
has recently stimulated increasing interest in applying it to address those challenges. Hence, in …
has recently stimulated increasing interest in applying it to address those challenges. Hence, in …
Wavelet-enhanced convolutional neural network: a new idea in a deep learning paradigm
BA Savareh, H Emami, M Hajiabadi… - Biomedical …, 2019 - degruyter.com
… Although the deep learning paradigm emphasizes on … , the advancement of deep learning
optimization algorithms can also … in order to enhance deep learning using other mathematical …
optimization algorithms can also … in order to enhance deep learning using other mathematical …
Deep learning for drug design: an artificial intelligence paradigm for drug discovery in the big data era
… the most successful implementations of the deep learning (DL) … deep learning architectures
has emerged as the first attempted technologies to address AI challenges (4). Deep learning …
has emerged as the first attempted technologies to address AI challenges (4). Deep learning …
Healthcare data analysis using deep learning paradigm
… deeper manner, the neural network under ML approach promotes a significant role. In-specific,
deep learning … and machine learning (AI/ML) paradigm that mimics how people learn. So, …
deep learning … and machine learning (AI/ML) paradigm that mimics how people learn. So, …