Results 21 to 30 of about 69,276 (264)
EffShuffNet: An Efficient Neural Architecture for Adopting a Multi-Model
Applied Sciences, 2023 This work discusses the challenges of multi-label image classification and presents a novel Efficient Shuffle Net (EffShuffNet) based on a convolutional neural network (CNN) architecture to address these challenges.
Jong-In Kim +7 more
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Efficient real-time detection of electrical equipment images using a lightweight detector model
Frontiers in Energy Research, 2023 Infrared technology holds significant importance in the detection of electrical equipment, as it has the capability to swiftly and securely identify electrical apparatus.
Chaoliang Qi +9 more
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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 +2 more
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GA-YOLO: A Lightweight YOLO Model for Dense and Occluded Grape Target Detection
Horticulturae, 2023 Picking robots have become an important development direction of smart agriculture, and the position detection of fruit is the key to realizing robot picking.
Jiqing Chen +6 more
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Lightweight Landslide Detection Network for Emergency Scenarios
Remote Sensing, 2023 Landslides are geological disasters that can cause serious severe damage to properties and lead to the loss of human lives. The application of deep learning technology to optical remote sensing images can help in the detection of landslide areas ...
Xuming Ge, Qian Zhao, Bin Wang, Min Chen
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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
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Sensors, 2023 During steel production, various defects often appear on the surface of the steel, such as cracks, pores, scars, and inclusions. These defects may seriously decrease steel quality or performance, so how to timely and accurately detect defects has great ...
Ji Wang +3 more
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Eye Semantic Segmentation with A Lightweight Model [PDF]
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019 In this paper, we present a multi-class eye segmentation method that can run the hardware limitations for real-time inference. Our approach includes three major stages: get a grayscale image from the input, segment three distinct eye region with a deep network, and remove incorrect areas with heuristic filters.
Huynh, Van Thong +3 more
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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 +4 more
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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 +5 more
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