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Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters
Computational tools for forecasting yields and prices for fresh produce ...
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On the Philosophical, Cognitive and Mathematical Foundations of Symbiotic Autonomous Systems (SAS)
Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitiv...
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Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey
Stochastic Neighbor Embedding (SNE) is a manifold learning and dimension...
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Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey
Multidimensional Scaling (MDS) is one of the first fundamental manifold ...
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A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation...
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Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem
Variants of Triplet networks are robust entities for learning a discrimi...
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Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches
We analyze the effect of offline and online triplet mining for colorecta...
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Roweisposes, Including Eigenposes, Supervised Eigenposes, and Fisherposes, for 3D Action Recognition
Human action recognition is one of the important fields of computer visi...
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Quantile-Quantile Embedding for Distribution Transformation, Manifold Embedding, and Image Embedding with Choice of Embedding Distribution
We propose a new embedding method, named Quantile-Quantile Embedding (QQ...
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Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces
After the tremendous development of neural networks trained by backpropa...
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Anomaly Detection and Prototype Selection Using Polyhedron Curvature
We propose a novel approach to anomaly detection called Curvature Anomal...
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Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks
Siamese neural network is a very powerful architecture for both feature ...
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Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders
Generative models and inferential autoencoders mostly make use of ℓ_2 no...
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Weighted Fisher Discriminant Analysis in the Input and Feature Spaces
Fisher Discriminant Analysis (FDA) is a subspace learning method which m...
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Roweis Discriminant Analysis: A Generalized Subspace Learning Method
We present a new method which generalizes subspace learning based on eig...
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Quantized Fisher Discriminant Analysis
This paper proposes a new subspace learning method, named Quantized Fish...
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Locally Linear Image Structural Embedding for Image Structure Manifold Learning
Most of existing manifold learning methods rely on Mean Squared Error (M...
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Principal Component Analysis Using Structural Similarity Index for Images
Despite the advances of deep learning in specific tasks using images, th...
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Fisher and Kernel Fisher Discriminant Analysis: Tutorial
This is a detailed tutorial paper which explains the Fisher discriminant...
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Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review
Pattern analysis often requires a pre-processing stage for extracting or...
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Eigenvalue and Generalized Eigenvalue Problems: Tutorial
This paper is a tutorial for eigenvalue and generalized eigenvalue probl...
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Addressing the Mystery of Population Decline of the Rose-Crested Blue Pipit in a Nature Preserve using Data Visualization
Two main methods for exploring patterns in data are data visualization a...
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Fitting A Mixture Distribution to Data: Tutorial
This paper is a step-by-step tutorial for fitting a mixture distribution...
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Improving Multi-Step Traffic Flow Prediction
In its simplest form, the traffic flow prediction problem is restricted ...
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SAFE: Spectral Evolution Analysis Feature Extraction for Non-Stationary Time Series Prediction
This paper presents a practical approach for detecting non-stationarity ...
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Semi-supervised Dictionary Learning Based on Hilbert-Schmidt Independence Criterion
In this paper, a novel semi-supervised dictionary learning and sparse re...
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Driver distraction detection and recognition using RGB-D sensor
Driver inattention assessment has become a very active field in intellig...
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