Results 51 to 60 of about 5,285,158 (212)
Visual tracking based on transfer learning of deep salience information
Opto-Electronic Advances, 2020 In this paper, we propose a new visual tracking method in light of salience information and deep learning. Salience detection is used to exploit features with salient information of the image.
Zuo Haorui +3 more
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Medical imaging analysis with artificial neural networks [PDF]
, 2010 Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection ...
Jiang, J., Ren, Jinchang, Trundle, P.
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EURASIP Journal on Image and Video Processing, 2018 UAV remote sensing has been widely used in emergency rescue, disaster relief, environmental monitoring, urban planning, and so on. Image recognition and image location in environmental monitoring has become an academic hotspot in the field of computer ...
Kunrong Zhao +6 more
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Optimized Layered Convolutional Sub-health Recognition Algorithm of Improved Capsule Network
Jisuanji kexue yu tansuo, 2021 Aiming at the problem that traditional convolutional neural network (CNN) continuously stacks convo-lutional layers and pooling layers in order to obtain high accuracy, resulting in complicated model structure, long training time, and single data ...
ZHANG Li, QIU Cunyue, ZHANG Kaixin, ZHANG Dabo, LUO Hao
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Non-linear coupled CNN models for multiscale image analysis [PDF]
, 2006 A CNN model of partial differential equations (PDEs) for image multiscale analysis is proposed. The model is based on a polynomial representation of the diffusivity function and defines a paradigm of polynomial CNNs,for approximating a large class of ...
Corinto, Fernando +2 more
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Annual dilated convolution neural network for newbuilding ship prices forecasting
, 2022 Anticipating newbuilding ship prices is crucial for participants in the dynamic shipping market. Although the researchers from forecasting and shipping have shown that the machine learning models outperform statistical ones, convolution neural networks ...
Yuen, Kum Fai +3 more
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Application of Convolutional Neural Network (CNN) to Recognize Ship Structures
Sensors, 2022 The purpose of this paper is to study the recognition of ships and their structures to improve the safety of drone operations engaged in shore-to-ship drone delivery service. This study has developed a system that can distinguish between ships and their structures by using a convolutional neural network (CNN).
Jae-Jun Lim +6 more
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An attention‐based cascade R‐CNN model for sternum fracture detection in X‐ray images
CAAI Transactions on Intelligence Technology, 2022 Fracture is one of the most common and unexpected traumas. If not treated in time, it may cause serious consequences such as joint stiffness, traumatic arthritis, and nerve injury.
Yang Jia +4 more
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ANALISIS PERFORMANSI CONVOLUTION NEURAL NETWORK (CNN) DAN NEURAL NETWORK (NN) TERHADAP IDENTIFIKASI TUJUH JENIS BUAH PIR [PDF]
, 2023 Pears are one of the fruits that people often consume Indonesia is the Asian pear (Pyrus pyrifolia) because pears have characteristics which is sweet, sour and crunchy is a fruit that is popular in Indonesia, because The high consumption of pears in ...
Setyawan, Handi Fajar
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Convolutional Neural Network (CNN) with Randomized Pooling
, 2022 Abstract Convolutional Neural Network (CNN) is a deep learning approach to solve complex problems, and it has been widely used in image processing for image classification, object identification, semantic segmentation etc. It has overcome the constraint of traditional machine learning approaches.
Hafiz Imran +2 more
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