Results 1 to 10 of about 690,616 (166)
Realizing Data Features by Deep Nets [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2020 This paper considers the power of deep neural networks (deep nets for short) in realizing data features. Based on refined covering number estimates, we find that, to realize some complex data features, deep nets can improve the performances of shallow neural networks (shallow nets for short) without requiring additional capacity costs.
Zheng-Chu Guo, Lei Shi, Shaobo Lin
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Applied Sciences, 2020 Brain tumor (BT) is one of the brain abnormalities which arises due to various reasons. The unrecognized and untreated BT will increase the morbidity and mortality rates.
Venkatesan Rajinikanth +3 more
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HFNet-SLAM: An Accurate and Real-Time Monocular SLAM System with Deep Features [PDF]
Sensors, 2023 Image tracking and retrieval strategies are of vital importance in visual Simultaneous Localization and Mapping (SLAM) systems. For most state-of-the-art systems, hand-crafted features and bag-of-words (BoW) algorithms are the common solutions.
Liming Liu, Jonathan M. Aitken
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Deep Features from Pretrained Networks Do Not Outperform Hand-Crafted Features in Radiomics [PDF]
Diagnostics, 2023 Aydin Demircioglu, Demircioglu Aydin
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On the Importance of Encrypting Deep Features [PDF]
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021 First ...
Xingyang Ni, Heikki Huttunen, Esa Rahtu
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A Variational Level Set Approach to Multiphase Multi-Object Tracking in Camera Network Base on Deep Features [PDF]
Journal of Electrical and Computer Engineering Innovations, 2021 Background and Objectives: Object tracking in video streams is one of the issues in machine vision that has many applications. Depending on the type of the object, the number of objects and other inputs used in tracking, object tracking is divided into ...
E. Pazouki, M. Rahmati
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Deep Probabilistic Feature-Metric Tracking [PDF]
IEEE Robotics and Automation Letters, 2021 Dense image alignment from RGB-D images remains a critical issue for real-world applications, especially under challenging lighting conditions and in a wide baseline setting. In this paper, we propose a new framework to learn a pixel-wise deep feature map and a deep feature-metric uncertainty map predicted by a Convolutional Neural Network (CNN), which
Binbin Xu 0001 +2 more
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Applied Sciences, 2022 Characterization of acoustic emission (AE) signals in loaded materials can reveal structural damage and consequently provide early warnings about product failures.
Primož Potočnik +4 more
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Image Retrieval Method Based on Image Feature Fusion and Discrete Cosine Transform
Applied Sciences, 2021 This paper presents a new content-based image retrieval (CBIR) method based on image feature fusion. The deep features are extracted from object-centric and place-centric deep networks. The discrete cosine transform (DCT) solves the strong correlation of
DaYou Jiang, Jongweon Kim
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Remote Sensing, 2022 Recent developments in remote sensing technology have allowed us to observe the Earth with very high-resolution (VHR) images. VHR imagery scene classification is a challenging problem in the field of remote sensing.
Souleyman Chaib +5 more
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