scholarly journals Object-Level Reasoning with Logics Encoded in HOL Light

2021 ◽  
Vol 332 ◽  
pp. 18-34
Author(s):  
Petros Papapanagiotou ◽  
Jacques Fleuriot
Keyword(s):  
Hol Light ◽  
Object Level

Object-level change detection based on full-scale image segmentation and its application to Wenchuan Earthquake

2008 ◽  
Vol 51 (S2) ◽  
pp. 110-122 ◽  
Author(s):  
JianYa Gong ◽  
HaiGang Sui ◽  
KaiMin Sun ◽  
GuoRui Ma ◽  
JunYi Liu
Keyword(s):  
Image Segmentation ◽  
Change Detection ◽  
Wenchuan Earthquake ◽  
Full Scale ◽  
Level Change ◽  
Object Level

Site-projected electronic structure of two-dimensional Ti3C2MXene: the role of the surface functionalization groups

2016 ◽  
Vol 18 (45) ◽  
pp. 30946-30953 ◽  
Author(s):  
Damien Magne ◽  
Vincent Mauchamp ◽  
Stéphane Célérier ◽  
Patrick Chartier ◽  
Thierry Cabioc'h
Keyword(s):  
Electronic Structure ◽  
Surface Functionalization ◽  
Chemical Bonding ◽  
Surface Groups ◽  
Two Dimensional ◽  
Object Level

The role of the surface groups in chemical bonding in two dimensional Ti3C2is evidenced at the nano-object level.

Saliency detection in computer rendered images based on object-level contrast

2014 ◽  
Vol 25 (3) ◽  
pp. 525-533 ◽  
Author(s):  
Lu Dong ◽  
Weisi Lin ◽  
Yuming Fang ◽  
Shiqian Wu ◽  
Hock Soon Seah
Keyword(s):  
Saliency Detection ◽  
Object Level

A Unified Approach of Object-Level Saliency Detection in Images and Videos

2013 ◽  
Vol 765-767 ◽  
pp. 1401-1405
Author(s):  
Chi Zhang ◽  
Wei Qiang Wang
Keyword(s):  
Quality Evaluation ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Unified Approach ◽  
Feature Maps ◽  
Still Images ◽  
Saliency Maps ◽  
Novel Method ◽  
Object Level ◽  
Important Branch

Object-level saliency detection is an important branch of visual saliency. In this paper, we propose a novel method which can conduct object-level saliency detection in both images and videos in a unified way. We employ a more effective spatial compactness assumption to measure saliency instead of the popular contrast assumption. In addition, we present a combination framework which integrates multiple saliency maps generated in different feature maps. The proposed algorithm can automatically select saliency maps of high quality according to the quality evaluation score we define. The experimental results demonstrate that the proposed method outperforms all state-of-the-art methods on both of the datasets of still images and video sequences.

Motion Detection of Webcam Using Frame Differencing Method

2021 ◽  
pp. 32-38
Author(s):  
Pooja Nagpal ◽  
Shalini Bhaskar Bajaj ◽  
Aman Jatain ◽  
Sarika Chaudhary
Keyword(s):  
Machine Learning ◽  
Motion Detection ◽  
Background Subtraction ◽  
Surveillance System ◽  
Detection Algorithm ◽  
Alert Message ◽  
Object Level

It is the capability of humans and as well as vehicles to automatically detect object level motion that results into collision less navigation and also provides sense of situation. This paper presents a technique for secure object level motion detection which yields more accurate results. To achieve this, python code has been used along with various machine learning libraries. The detection algorithm uses the advantage of background subtraction and fed in data to detect even the slightest movement this system makes use of a webcam to scan a premise and detect movement of any sort; on the recognition of any activity it immediately sends an alert message to the owner of the system via mail. Any person requiring a surveillance system can use it.

Formalization of Geometric Algebra in HOL Light

2018 ◽  
Vol 63 (3) ◽  
pp. 787-808
Author(s):  
Li-Ming Li ◽  
Zhi-Ping Shi ◽  
Yong Guan ◽  
Qian-Ying Zhang ◽  
Yong-Dong Li
Keyword(s):  
Geometric Algebra ◽  
Hol Light
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