Search
Search Results
-
Adaptive Discriminant and Quasiconformal Kernel Nearest Neighbor Classification
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to...
-
Clustering with Intelligent Techniques
Cluster analysis is a technique for grou** data and finding structures in data. The most common application of clustering methods is to partition a...
-
Active-Set Methods for Support Vector Machines
This chapter describes an active-set algorithm for quadratic programming problems that arise from the computation of support vector machines (SVMs)....
-
Local Learning vs. Global Learning: An Introduction to Maxi-Min Margin Machine
We present a unifying theory of the Maxi-Min Margin Machine (M4) that subsumes the Support Vector Machine (SVM), the Minimax Probability Machine...
-
Application of Support Vector Machine to the Detection of Delayed Gastric Emptying from Electrogastrograms
The radioscintigraphy is currently the gold standard for gastric emptying test, but it involves radiation exposure and considerable expenses. Recent...
-
An Accelerated Robust Support Vector Machine Algorithm
This chapter proposes an accelerated decomposition algorithm for robust support vector machine (SVM). Robust SVM aims at solving the overfitting...
-
Unsupervised Learning Neural Networks
This chapter introduces the basic concepts and notation of unsupervised learning neural networks. Unsupervised networks are useful for analyzing data...
-
Evolutionary Computing for Architecture Optimization
This chapter introduces the basic concepts and notation of evolutionary algorithms, which are basic search methodologies that can be used for...
-
Introduction to Pattern Recognition with Intelligent Systems
We describe in this book, new methods for intelligent pattern recognition using soft computing techniques. Soft Computing (SC) consists of several...
-
Supervised Learning Neural Networks
In this chapter, we describe the basic concepts, notation, and basic learning algorithms for supervised neural networks that will be of great use for...
-
Face Recognition with Modular Neural Networks and Fuzzy Measures
We describe in this chapter a new approach for face recognition using modular neural networks with a fuzzy logic method for response integration. We...
-
Intuitionistic and Type-2 Fuzzy Logic
We describe in this chapter two new areas in fuzzy logic, type-2 fuzzy logic systems and intuitionistic fuzzy logic. Basically, a type-2 fuzzy set is...
-
A resource-efficient partial 3D convolution for gesture recognition
3DCNNs have shown impressive capabilities in extracting spatiotemporal features from videos. However, in practical applications, the numerous...
-
Aspect-based drug review classification through a hybrid model with ant colony optimization using deep learning
The task of aspect-level sentiment analysis is intricately designed to determine the sentiment polarity directed towards a specific target within a...
-
Scene text recognition: an Indic perspective
Exploring Scene Text Recognition (STR) in Indian languages is an important research domain due to its wide applications. This paper proposes a...
-
Procedure-Aware Action Quality Assessment: Datasets and Performance Evaluation
In this paper, we investigate the problem of procedure-aware action quality assessment, which analyzes the action quality by delving into the...
-
Fast Global Image Smoothing via Quasi Weighted Least Squares
Image smoothing is a long-studied research area with tremendous approaches proposed. However, how to perform high-quality image smoothing with less...
-
Multi-modal Prototypes for Open-World Semantic Segmentation
In semantic segmentation, generalizing a visual system to both seen categories and novel categories at inference time has always been practically...
-
End-to-End Video Text Spotting with Transformer
Recent video text spotting methods usually require the three-staged pipeline, i.e., detecting text in individual images, recognizing localized text,...
-
CD-iNet: Deep Invertible Network for Perceptual Image Color Difference Measurement
Image color difference (CD) measurement, a crucial concept in color science and imaging technology, aims to quantify the perceived difference between...
