Results 51 to 60 of about 3,136,925 (183)

Link Prediction with Mutual Attention for Text-Attributed Networks

, 2019
In this extended abstract, we present an algorithm that learns a similarity measure between documents from the network topology of a structured corpus.
Brochier, Robin, Guille, Adrien, Velcin, Julien   +2 more
core   +3 more sources

Swarmic Sketches and Attention Mechanism [PDF]

, 2013
This paper introduces a novel approach deploying the mechanism of ‘attention’ by adapting a swarm intelligence algorithm – Stochastic Diffusion Search – to selectively attend to detailed areas of a digital canvas. Once the attention of the swarm is drawn to a certain line within the canvas, the capability of another swarm intelligence algorithm ...
Al-Rifaie, Mohammad Majid, Bishop, Mohammad   +1 more
openaire   +2 more sources

Probabilistic Attention Map: A Probabilistic Attention Mechanism for Convolutional Neural Networks

Sensors
The attention mechanism is essential to convolutional neural network (CNN) vision backbones used for sensing and imaging systems. Conventional attention modules are designed heuristically, relying heavily on empirical tuning.
Yifeng Liu, Jing Tian
doaj   +1 more source

Macaron Attention: The Local Squeezing Global Attention Mechanism in Tracking Tasks

Remote Sensing
The Unmanned Aerial Vehicle (UAV) tracking tasks find extensive utility across various applications. However, current Transformer-based trackers are generally tailored for diverse scenarios and lack specific designs for UAV applications. Moreover, due to
Zhixing Wang, Hui Luo, Dongxu Liu, Meihui Li, Yunfeng Liu, Qiliang Bao, Jianlin Zhang   +6 more
doaj   +1 more source

A dual attention mechanism semantic segmentation method for autonomous driving

Xi'an Gongcheng Daxue xuebao, 2023
The paper introduces a refined dual attention mechanism designed to mitigate attention deficiency challenges encountered during the segmentation of diminutive objects within the domain of autonomous driving.
WANG Yannian, RUAN Pei, LIAN Jihong, ZHENG Fangliang   +3 more
doaj   +1 more source

Attention to Monkeypox: An Interpretable Monkeypox Detection Technique Using Attention Mechanism

IEEE Access
In the wake of COVID-19, rising monkeypox cases pose a potential pandemic threat. While less severe than COVID-19, its increasing spread underscores the urgency of early detection and isolation to control the disease.
Avi Deb Raha, Mrityunjoy Gain, Rameswar Debnath, Apurba Adhikary, Yu Qiao, Md. Mehedi Hassan, Anupam Kumar Bairagi, Sheikh Mohammed Shariful Islam   +7 more
doaj   +1 more source

Scale Pyramid Attention for Single Shot MultiBox Detector

IEEE Access, 2019
Feature pyramid mechanism has improved the performance of object detectors by a large margin, especially for the objects with small scale. As one of the first attempts to use pyramidal feature hierarchy, Single Shot MultiBox Detector (SSD) has largely ...
Jie Hao, Feng Jiang, Rufei Zhang, Xipeng Lin, Biao Leng, Guanglu Song   +5 more
doaj   +1 more source

Double Attention: An Optimization Method for the Self-Attention Mechanism Based on Human Attention

Biomimetics
Artificial intelligence, with its remarkable adaptability, has gradually integrated into daily life. The emergence of the self-attention mechanism has propelled the Transformer architecture into diverse fields, including a role as an efficient and ...
Zeyu Zhang, Bin Li, Chenyang Yan, Kengo Furuichi, Yuki Todo   +4 more
doaj   +1 more source

Attention-Based LSTM for Psychological Stress Detection from Spoken Language Using Distant Supervision

, 2018
We propose a Long Short-Term Memory (LSTM) with attention mechanism to classify psychological stress from self-conducted interview transcriptions.
Fung, Pascale, Kampman, Onno Pepijn, Winata, Genta Indra   +2 more
core   +1 more source

Visual Attention Mechanism for a Social Robot

Applied Bionics and Biomechanics, 2012
This paper describes a visual perception system for a social robot. The central part of this system is an artificial attention mechanism that discriminates the most relevant information from all the visual information perceived by the robot.
Juan Pedro Bandera, R. Marfil, Antonio Jesús Palomino, Ricardo Vázquez-Martín, Antonio Bandera   +4 more
doaj   +1 more source