Object Detection Using Multi-Scale Balanced Sampling
نویسندگان
چکیده
منابع مشابه
Global-scale Object Detection Using Satellite Imagery
In recent years, there has been a substantial increase in the availability of high-resolution commercial satellite imagery, enabling a variety of new remote-sensing applications. One of the main challenges for these applications is the accurate and efficient extraction of semantic information from satellite imagery. In this work, we investigate an important instance of this class of challenges ...
متن کاملObject Detection Based on Multi-scale Contour Fragments
In this paper, we present a novel object detection scheme using the multi-scale contour fragments. The template fragments are extracted by decomposing the template contour. The multi-scale hinge angle, contour direction and partial Hausdorff distance (PHD) are used to select candidates in the edge image. Then, the matches with different scales and directions are selected by the Multiclass Discr...
متن کاملMulti-scale Location-aware Kernel Representation for Object Detection
Although Faster R-CNN and its variants have shown promising performance in object detection, they only exploit simple first-order representation of object proposals for final classification and regression. Recent classification methods demonstrate that the integration of highorder statistics into deep convolutional neural networks can achieve impressive improvement, but their goal is to model w...
متن کاملMSDNN: Multi-Scale Deep Neural Network for Salient Object Detection
Salient object detection is a fundamental problem and has been received a great deal of attentions in computer vision. Recently deep learning model became a powerful tool for image feature extraction. In this paper, we propose a multi-scale deep neural network (MSDNN) for salient object detection. The proposed model first extracts global high-level features and context information over the whol...
متن کاملMulti-scale volumes for deep object detection and localization
This study aims to analyze the benefits of improved multiscale reasoning for object detection and localization with deep convolutional neural networks. To that end, an efficient and general object detection framework which operates on scale volumes of a deep feature pyramid is proposed. In contrast to the proposed approach, most current state-of-the-art object detectors operate on a single-scal...
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: Applied Sciences
سال: 2020
ISSN: 2076-3417
DOI: 10.3390/app10176053