Sediment Classification of Acoustic Backscatter Image Based on Stacked Denoising Autoencoder and Modified Extreme Learning Machine
نویسندگان
چکیده
منابع مشابه
Remote Sensing Image Classification Based on Stacked Denoising Autoencoder
Focused on the issue that conventional remote sensing image classification methods have run into the bottlenecks in accuracy, a new remote sensing image classification method inspired by deep learning is proposed, which is based on Stacked Denoising Autoencoder. First, the deep network model is built through the stacked layers of Denoising Autoencoder. Then, with noised input, the unsupervised ...
متن کاملRadar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine
A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve g...
متن کاملRelational Stacked Denoising Autoencoder for Tag Recommendation
Tag recommendation has become one of the most important ways of organizing and indexing online resources like articles, movies, and music. Since tagging information is usually very sparse, effective learning of the content representation for these resources is crucial to accurate tag recommendation. Recently, models proposed for tag recommendation, such as collaborative topic regression and its...
متن کاملA New Denoising Algorithm Based on Extreme Learning Machine
A new image denoising algorithm is proposed. GA-ELM algorithm uses genetic algorithm (GA) to decide weights in the Extreme learning Machine algorithm. It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-ELM to do image denoising researching work. Firstly, this paper uses training samples to train GA-ELM as the noise detector. Then, we utili...
متن کاملStacked Robust Autoencoder for Classification
In this work we propose an lp-norm data fidelity constraint for training the autoencoder. Usually the Euclidean distance is used for this purpose; we generalize the l2-norm to the lp-norm; smaller values of p make the problem robust to outliers. The ensuing optimization problem is solved using the Augmented Lagrangian approach. The proposed lp -norm Autoencoder has been tested on benchmark deep...
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: Remote Sensing
سال: 2020
ISSN: 2072-4292
DOI: 10.3390/rs12223762