Representation Learning Based on Autoencoder and Deep Adaptive Clustering for Image Clustering
نویسندگان
چکیده
منابع مشابه
An Adaptive LEACH-based Clustering Algorithm for Wireless Sensor Networks
LEACH is the most popular clastering algorithm in Wireless Sensor Networks (WSNs). However, it has two main drawbacks, including random selection of cluster heads, and direct communication of cluster heads with the sink. This paper aims to introduce a new centralized cluster-based routing protocol named LEACH-AEC (LEACH with Adaptive Energy Consumption), which guarantees to generate balanced cl...
متن کاملSupplementary Material: Deep Adaptive Image Clustering
This is the supplementary material for the paper entitled “Deep Adaptive Image Clustering”. The supplementary material is organized as follows. Section 1 gives the mapping function described in Figure 1. Section 2 presents the proof of Theorem 1. Section 3 details the experimental settings in our experiments. 1. The Mapping Function Utilized in Figure 1 We assume that li represents the label fe...
متن کاملSemi-supervised Clustering for Short Text via Deep Representation Learning
In this work, we propose a semi-supervised method for short text clustering, where we represent texts as distributed vectors with neural networks, and use a small amount of labeled data to specify our intention for clustering. We design a novel objective to combine the representation learning process and the kmeans clustering process together, and optimize the objective with both labeled data a...
متن کاملUnsupervised Learning of Deep Feature Representation for Clustering Egocentric Actions
Popularity of wearable cameras in life logging, law enforcement, assistive vision and other similar applications is leading to explosion in generation of egocentric video content. First person action recognition is an important aspect of automatic analysis of such videos. Annotating such videos is hard, not only because of obvious scalability constraints, but also because of privacy issues ofte...
متن کاملLatent Tree Variational Autoencoder for Joint Representation Learning and Multidimensional Clustering
Recently, deep learning based clustering methods are shown superior to traditional ones by jointly conducting representation learning and clustering. These methods rely on the assumptions that the number of clusters is known, and that there is one single partition over the data and all attributes define that partition. However, in real-world applications, prior knowledge of the number of cluste...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2021
ISSN: 1563-5147,1024-123X
DOI: 10.1155/2021/3742536