Results 31 to 40 of about 104,305 (311)

Ship Fire Detection Based on an Improved YOLO Algorithm with a Lightweight Convolutional Neural Network Model

Sensors, 2022
Ship fire is one of the greatest dangers to ship navigation safety. Nevertheless, typical detection methods have limited detection effectiveness and accuracy due to distance restrictions and ship motion.
Huafeng Wu, Yanglin Hu, Weijun Wang, Xiaojun Mei, Jiangfeng Xian   +4 more
doaj   +1 more source

Lightweight Source Model Extraction [PDF]

, 1995
Reverse engineers depend on the automatic extraction of information from source code. Some useful kinds of information---source models---are wellknown: call graphs, file dependences, etc.
David Notkin, Gail C. Murphy, Gail Murphy   +2 more
core   +1 more source

DSANet: A Deep Supervision-Based Simple Attention Network for Efficient Semantic Segmentation in Remote Sensing Imagery

Remote Sensing, 2022
Semantic segmentation for remote sensing images (RSIs) plays an important role in many applications, such as urban planning, environmental protection, agricultural valuation, and military reconnaissance.
Wenxu Shi, Qingyan Meng, Linlin Zhang, Maofan Zhao, Chen Su, Tamás Jancsó   +5 more
doaj   +1 more source

Very Lightweight Requirements Modeling

2010 18th IEEE International Requirements Engineering Conference, 2010
We argue for the creation and use of a very lightweight requirements modeling language as an alternative to textual and pictorial requirements specifications.
openaire   +2 more sources

Lightweight Asymmetric Dilation Network for Real-Time Semantic Segmentation

IEEE Access, 2021
Semantic segmentation is a very important and challenging problem in computer vision. Many applications, such as automated driving and robotic navigation in urban road scenes, require accurate and efficient segmentation. Nowadays, system models are often
Xuegang Hu, Yu Gong
doaj   +1 more source

LFMNet: a lightweight model for identifying leaf diseases of maize with high similarity. [PDF]

Front Plant Sci
Hu J, Jiang X, Gao J, Yu X.
europepmc   +2 more sources

A Lightweight CNN Model Based on GhostNet

Computational Intelligence and Neuroscience, 2022
The existing deep learning models have problems such as large weight parameters and slow inference speed of equipment. In practical applications such as fire detection, they often cannot be deployed on equipment with limited resources due to the huge amount of parameters and low efficiency. In response to this problem, this paper proposes a lightweight
Zhong Wang, Tong Li
openaire   +2 more sources

Lightweight Tunnel Obstacle Detection Based on Improved YOLOv5

Sensors
Considering the high incidence of accidents at tunnel construction sites, using robots to replace humans in hazardous tasks can effectively safeguard their lives.
Yingjie Li, Chuanyi Ma, Liping Li, Rui Wang, Zhihui Liu, Zizheng Sun   +5 more
doaj   +1 more source

Flexible, lightweight requirements modeling with Flexisketch

2012 20th IEEE International Requirements Engineering Conference (RE), 2012
Early stage requirements models are often documented using paper and pencil-based approaches. In our current research, we are exploring lightweight modeling tools and approaches that could provide a beneficial alternative. We have developed the FlexiSketch tool prototype which combines support for free-form sketching with lightweight metamodeling ...
Wüest, Dustin, Seyff, Norbert, Glinz, Martin   +2 more
openaire   +1 more source

Lightweight Statistical Model Checking in Nondeterministic Continuous Time (Artifact)

, 2018
In our ISoLA 2018 paper titled "Lightweight Statistical Model Checking in Nondeterministic Continuous Time", we describe the challenges and state of the art in applying lightweight scheduler sampling to three continuous-time formalisms: After a review of
Hartmanns, A. (Arnd)
core   +1 more source