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Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics.
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Abstract
- Summary: The present reprint contains 33 articles accepted and published in the Special Issue entitled "Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics, 2022" in the MDPI journal, Mathematics, which covers a wide range of topics connected to the theory and applications of feature representation learning for image processing, artificial intelligence, data mining and robotics. These topics include, among others, elements from image blurring, image aesthetic quality assessment, pedestrian detection, visual tracking, vehicle re-identification, face recognition, 3D reconstruction, the stability of switched systems, domain adaption, deep reinforcement, sentiment analysis, graph convolutional networks, knowledge graphs, geometric metric learning, etc. It is hoped that this reprint will be interesting and useful for those working in the area of image processing, computer vision, machine learning, natural language processing and robotics, as well as for those with backgrounds in machine learning who are willing to become familiar with recent advancements in artificial intelligence, which, today, is present in almost all aspects of human life and activities.
- Subjects :
- Computer science
Information technology industries
3D reconstruction
ADMM
Aspect Level Sentiment Classification
C-MAPSS
Contrasitve Learning
DCNN-BiLSTM
Dempster-Shafer evidence theory
GAT
GCN
Graph Convolutional Networks
KGE
MMD
NMS
Soft-NMS
XSS attack
YOLOX
YoloV4
adversarial equilibrium
adversarial example
adversarial learning
anchor-free
anomaly detection
anti-noise performance
aspect-based sentiment analysis
aspect-level sentiment classification
attention mechanism
background matting
black-box attack
blind image deblurring
collaborative-representation-based classification
commonsense knowledge graph
computer vision
confidence score
contrastive learning
correlation filters
cost-weighted
cross-domain classification
cross-domain sentiment classification
cross-working
cyber-physical
data analysis
decoupling
deep learning
deep neural network
deep reinforcement learning
dependency trees
dependency types
discriminative feature learning
domain adaptation
elastic optical networks
end-to-end
ensemble attack
extension theory
external knowledge
face recognition
feature extraction
feature reuse
feature transformation
fine-tuning
fusion verification
fuzzy k-means
gait adjustment
garbage quantity identification
gated learning
geometric mean metric
graph attention mechanism
graph convolutional networks
graph neural networks
hate speech detection
head detection
hypergraph matching
image aesthetic assessment
image classification
image gradient orientations
image prior
image super-resolution
industrial control systems
information-theoretic metric learning
intelligent design
iterative majorization algorithm
joint semantic learning
kNN
knowledge distillation
knowledge graph embedding
label propagation
large-margin technique
license plate recognition
logarithm norm
low-high level joint task
machine learning
matrix nuclear norm
metric learning
mixed noise removal
models and algorithms
motion deblurring
multi-order attention
multi-output
multi-source domain adaptation
multi-task learning
multi-view stereo
multidimensional scaling
n/a
object detection
pairwise constraint propagation
payloads
pedestrian detection
people counting
plug-and-play
power load forecasting
rainy image recovery
robustness
routing, modulation and spectrum assignment
scheme design
second-order fitting
second-order gradient
semantic
semi-supervised learning
similarity metric
small sample
soft-NMS
sparse channel
sparsity
stability
state reconstruction
state-dependent switching
structure from motion
switched system
syntactic
temporal knowledge graph
time delay
traffic detection
transferability quantification
uncertain temporal knowledge graph
vehicle color recognition
vehicle re-identification
video surveillance
visual tracking
word embedding
Subjects
Details
- Language :
- English
- ISBN :
- 9783036572628
9783036572635
books978-3-0365-7263-5 - ISBNs :
- 9783036572628, 9783036572635, and 9783036572635
- Database :
- Jio Institute Digital Library OPAC
- Journal :
- Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics
- Notes :
- 004364, Journalism, Open Access star Unrestricted online access, Creative Commons https://creativecommons.org/licenses/by/4.0/ cc https://creativecommons.org/licenses/by/4.0/, English
- Publication Type :
- eBook
- Accession number :
- jio.Koha.JDL.137
- Document Type :
- Book; Electronic document