Cover Image
Read Now

Innovative Topologies and Algorithms for Neural Networks

The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text process...

Full description

Bibliographic Details
Main Author: Xibilia, Maria Gabriella
Other Authors: Graziani, Salvatore
Format: eBook
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Tooth-marked Tongue
Deep Convolutional Neural Networks
Linguistic Features
Gradient-weighted Class Activation Maps
Feature Fusion
Motion Map
Object Detection Network
Human Computer Interaction
Long Short-term-memory
Deep Learning
Pedestrian Attribute Recognition
Ship Identification
3d Convolution Neural Network
Lstm
Iot (internet Of Thing) Systems
Bidirectional Gated Recurrent Unit
Graph Convolutional Network
Graph Partitioning
Internet Of Things
Information Technology Industries / Bicssc
Embedded Deep Learning
Attention Mechanism
Scalability
Facial Nerve Paralysis
Distributed Systems
Resource-efficient Inference
Pos Syntactic Rules
Sentiment Analysis
Alternative Fusion Neural Network
Object Recognition
Arabic Named Entity Recognition
Gesture Recognition
Bidirectional Recurrent Neural Network
Convolutional Neural Networks
Elements Recognition
Long-short-term Memory Networks
Gru
Fused Features
Chinese Text Classification
Multi-label Learning
Action Recognition
Cnn
Long Short-term Memory
Medical Applications
Image Classification
Text Recognition
Natural Language Processing
Autoencoders
Convolutional Neural Network
Convolution Neural Networks
Word Embedding
Fully Convolutional Network
Lstm-crf Model
Facial Image Analysis
Sentiment Attention Mechanism
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Things). The probability of a successful outcome from a neural network is linked to selection of an appropriate network architecture and training algorithm. Accordingly, much of the recent research on neural networks has been devoted to the study and proposal of novel architectures, including solutions tailored to specific problems. This book gives significant contributions to the above-mentioned fields by merging theoretical aspects and relevant applications.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (198 p.)
ISBN:books978-3-0365-0285-4
9783036502854
9783036502847

Similar Items