Amanote Research

Amanote Research

    RegisterSign In

Segmenting Natural Images With the Least Effort as Humans

doi 10.5244/c.29.110
Full Text
Open PDF
Abstract

Available in full text

Date

January 1, 2015

Authors
Qiyang Zhao
Publisher

British Machine Vision Association


Related search

Watercolor, Segmenting Images Using Connected Color Components

2018English

Suitability of Digital Elevation Models for Watershed Segmenting Images With Directional Illumination

International Journal of Computer Applications
2013English

Ritual as Interaction With Non-Humans: Ritual as Interaction With Non-Humans

2017English

A New Open Source Toolkit for Segmenting 3D Intracellular Structures in Microscopy Images

Biophysical Journal
Biophysics
2019English

Choice of Equal Effects With Unequal Efforts: A Way to Quantify the Law of Least Effort

Bulletin of the Psychonomic Society
1981English

A New Adaptive Probabilistic Model of Blood Vessels for Segmenting MRA Images

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2006English

The Statistics of Natural Images

Network: Computation in Neural Systems
Neuroscience
1994English

Respiratory Effort Sensation During Exercise With Induced Expiratory-Flow Limitation in Healthy Humans

Journal of Applied Physiology
MedicinePhysiologySports Science
1997English

Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology

Language
LinguisticsLanguage
1950English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy