Results 41 to 50 of about 104,305 (311)

SATIN: a component model for mobile self-organisation [PDF]

, 2004
We have recently witnessed a growing interest in self organising systems, both in research and in practice. These systems re-organise in response to new or changing conditions in the environment.
Zachariadis, S., Mascolo, C., Cecilia Mascolo, Stefanos Zachariadis, Wolfgang Emmerich, Emmerich, W.   +5 more
core   +1 more source

Attention-Based Lightweight YOLOv8 Underwater Target Recognition Algorithm

Sensors
Underwater object detection is highly complex and requires a high speed and accuracy. In this paper, an underwater target detection model based on YOLOv8 (SPSM-YOLOv8) is proposed. It solves the problems of high computational complexities, slow detection
Shun Cheng, Zhiqian Wang, Shaojin Liu, Yan Han, Pengtao Sun, Jianrong Li   +5 more
doaj   +1 more source

A Lightweight Feature Optimizing Network for Ship Detection in SAR Image

IEEE Access, 2019
Deep learning-based methods have achieved great success in target detection tasks of computer vision, but when it comes to Synthetic Aperture Radar (SAR) image ship detection, some new challenges appear because of the wide swath of images, diverse ...
Xiaohan Zhang, Haipeng Wang, Congan Xu, Yafei Lv, Chunlong Fu, Huachao Xiao, You He   +6 more
doaj   +1 more source

Toward Efficient UAV-Based Small Object Detection: A Lightweight Network with Enhanced Feature Fusion

Remote Sensing
UAV-based small target detection is crucial in environmental monitoring, circuit detection, and related applications. However, UAV images often face challenges such as significant scale variation, dense small targets, high inter-class similarity, and ...
Xingyu Di, Kangning Cui, Rui-Feng Wang
doaj   +1 more source

A Lightweight Model for 3D Point Cloud Object Detection

, 2023
With the rapid development of deep learning, more and more complex models are applied to 3D point cloud object detection to improve accuracy. In general, the more complex the model, the better the performance and the greater the computational resource ...
Yang Li, Zhuoyang Lyu, Guangda Xie, Hongquan Qu, Ziyi Li, Yanping Wang   +5 more
core   +1 more source

Lightweight diffusion models: a survey

Artificial Intelligence Review
AbstractDiffusion models (DMs) are a type of potential generative models, which have achieved better effects in many fields than traditional methods. DMs consist of two main processes: one is the forward process of gradually adding noise to the original data until pure Gaussian noise; the other is the reverse process of gradually removing noise to ...
Wei Song, Wen Ma, Ming Zhang, Yanghao Zhang, Xiaobing Zhao   +4 more
openaire   +1 more source

Revisiting Stability Criteria in Ball‐Milled High‐Entropy Alloys: Do Hume–Rothery and Thermodynamic Rules Equally Apply?

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
The stability criteria affecting the formation of high‐entropy alloys, particularly focusing in supersaturated solid solutions produced by mechanical alloying, are analyzed. Criteria based on Hume–Rothery rules are distinguished from those derived from thermodynamic relations. The formers are generally applicable to mechanically alloyed samples.
Javier S. Blázquez, Alejandro F. Manchón‐Gordón, Antonio Vidal‐Crespo, Rafael Caballero‐Flores, Jhon J. Ipus, Clara F. Conde   +5 more
wiley   +1 more source

WATER WITHIN LIGHTWEIGHT AGGREGATE CONCRETE AND ITS RELATION TO AUTOGENOUS SHRINKAGE [PDF]

, 2006
Autogenous shrinkage of lightweight aggregate concrete (LAC) has been investigated with the aims of studying if water within LAC is effective in preventing autogenous shrinkage as suggested by Bentz’s model.
Kristiawan, S A, Sangadji, Senot
core  

YOLOv8n-SMMP: A Lightweight YOLO Forest Fire Detection Model

Fire
Global warming has driven a marked increase in forest fire occurrences, underscoring the critical need for timely and accurate detection to mitigate fire-related losses.
Nianzu Zhou, Demin Gao, Zhengli Zhu
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source