Co-Training for Deep Object Detection: Comparing Single-Modal and Multi-Modal Approaches

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Damage detection of multi-girder bridge superstructure based on the modal strain approaches

The research described in this paper focuses on the application of modal strain techniques on a multi-girder bridge superstructure with the objectives of identifying the presence of damage and detecting false damage diagnosis for such structures. The case study is a one-third scale model of a slab-on-girder composite bridge superstructure, comprised of a steel-free concrete deck with FRP rebars...

متن کامل

Multi-modal Deep Learning Approach for Flood Detection

In this paper we propose a multi-modal deep learning approach to detect floods in social media posts. Social media posts normally contain somemetadata and/or visual information, therefore in order to detect the floods we use this information. The model is based on a Convolutional Neural Network which extracts the visual features and a bidirectional Long Short-Term Memory network to extract the ...

متن کامل

Multi-modal Tracking for Object based SLAM

We present an on-line 3D visual object tracking framework for monocular cameras by incorporating spatial knowledge and uncertainty from semantic mapping along with high frequency measurements from visual odometry. Using a combination of vision and odometry that are tightly integrated we can increase the overall performance of object based tracking for semantic mapping. We present a framework fo...

متن کامل

Co-inference for Multi-modal Scene Analysis

We address the problem of understanding scenes from multiple sources of sensor data (e.g., a camera and a laser scanner) in the case where there is no one-to-one correspondence across modalities (e.g., pixels and 3-D points). This is an important scenario that frequently arises in practice not only when two different types of sensors are used, but also when the sensors are not co-located and ha...

متن کامل

Co-Regularized PLSA for Multi-Modal Learning

Many learning problems in real world applications involve rich datasets comprising multiple information modalities. In this work, we study co-regularized PLSA (coPLSA) as an efficient solution to probabilistic topic analysis of multi-modal data. In coPLSA, similarities between topic compositions of a data entity across different data modalities are measured with divergences between discrete pro...

متن کامل

ذخیره 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: Sensors

سال: 2021

ISSN: 1424-8220

DOI: 10.3390/s21093185