Interpretation of intelligence in CNN-pooling processes: a methodological survey
N Akhtar, U Ragavendran - Neural computing and applications, 2020 - Springer
The convolutional neural network architecture has different components like convolution and
pooling. The pooling is crucial component placed after the convolution layer. It plays a vital …
pooling. The pooling is crucial component placed after the convolution layer. It plays a vital …
Deep learning approaches and interventions for futuristic engineering in agriculture
With shrinking natural resources and the climate challenges, it is foreseen that there will be
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …
The state-of-art of the generalizations of the Choquet integral: From aggregation and pre-aggregation to ordered directionally monotone functions
In 2013, Barrenechea et al. used the Choquet integral as an aggregation function in the
fuzzy reasoning method (FRM) of fuzzy rule-based classification systems. After that, starting …
fuzzy reasoning method (FRM) of fuzzy rule-based classification systems. After that, starting …
[HTML][HTML] Replacing pooling functions in Convolutional Neural Networks by linear combinations of increasing functions
Abstract Traditionally, Convolutional Neural Networks make use of the maximum or
arithmetic mean in order to reduce the features extracted by convolutional layers in a …
arithmetic mean in order to reduce the features extracted by convolutional layers in a …
Motor-imagery-based brain–computer interface using signal derivation and aggregation functions
Brain–computer interface (BCI) technologies are popular methods of communication
between the human brain and external devices. One of the most popular approaches to BCI …
between the human brain and external devices. One of the most popular approaches to BCI …
Sugeno integral generalization applied to improve adaptive image binarization
Classic adaptive binarization methodologies threshold pixels intensity with respect to
adjacent pixels exploiting integral images. In turn, integral images are generally computed …
adjacent pixels exploiting integral images. In turn, integral images are generally computed …
The Bonferroni mean-type pre-aggregation operators construction and generalization: Application to edge detection
In recent years, immense interest in the exploration of the generalized version of the
monotonicity condition has been significantly accomplished by the researchers. The …
monotonicity condition has been significantly accomplished by the researchers. The …
VCI-LSTM: Vector Choquet integral-based long short-term memory
Choquet integral is a widely used aggregation operator on 1-D and interval-valued
information, since it is able to take into account the possible interaction among data …
information, since it is able to take into account the possible interaction among data …
A study of OWA operators learned in convolutional neural networks
Ordered Weighted Averaging (OWA) operators have been integrated in Convolutional
Neural Networks (CNNs) for image classification through the OWA layer. This layer lets the …
Neural Networks (CNNs) for image classification through the OWA layer. This layer lets the …
The use of CLAHE for improving an accuracy of CNN architecture for detecting pneumonia
EA Tjoa, IPYN Suparta, R Magdalena… - SHS Web of …, 2022 - shs-conferences.org
Artificial intelligence (AI) has now grown rapidly for hel** many aspects of human life, one
of them is for medical image processing. Currently, the world is still suffering from COVID-19 …
of them is for medical image processing. Currently, the world is still suffering from COVID-19 …