Activation functions in deep learning: A comprehensive survey and benchmark
Neural networks have shown tremendous growth in recent years to solve numerous
problems. Various types of neural networks have been introduced to deal with different types …
problems. Various types of neural networks have been introduced to deal with different types …
A comparison of pooling methods for convolutional neural networks
One of the most promising techniques used in various sciences is deep neural networks
(DNNs). A special type of DNN called a convolutional neural network (CNN) consists of …
(DNNs). A special type of DNN called a convolutional neural network (CNN) consists of …
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Biologically informed deep neural network for prostate cancer discovery
The determination of molecular features that mediate clinically aggressive phenotypes in
prostate cancer remains a major biological and clinical challenge,. Recent advances in …
prostate cancer remains a major biological and clinical challenge,. Recent advances in …
Impact of fully connected layers on performance of convolutional neural networks for image classification
Abstract The Convolutional Neural Networks (CNNs), in domains like computer vision,
mostly reduced the need for handcrafted features due to its ability to learn the problem …
mostly reduced the need for handcrafted features due to its ability to learn the problem …
Video transformers: A survey
Transformer models have shown great success handling long-range interactions, making
them a promising tool for modeling video. However, they lack inductive biases and scale …
them a promising tool for modeling video. However, they lack inductive biases and scale …
Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions
In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …
(DL) computing model as the Gold Standard. DL has gradually become the most widely …
Graphene memristive synapses for high precision neuromorphic computing
Memristive crossbar architectures are evolving as powerful in-memory computing engines
for artificial neural networks. However, the limited number of non-volatile conductance states …
for artificial neural networks. However, the limited number of non-volatile conductance states …
Interpreting biologically informed neural networks for enhanced proteomic biomarker discovery and pathway analysis
The incorporation of machine learning methods into proteomics workflows improves the
identification of disease-relevant biomarkers and biological pathways. However, machine …
identification of disease-relevant biomarkers and biological pathways. However, machine …
Classification of sour lemons based on apparent defects using stochastic pooling mechanism in deep convolutional neural networks
Quality assessment of agricultural products is one of the most important factors in promoting
their marketability and waste control management. Image processing systems are new and …
their marketability and waste control management. Image processing systems are new and …