this work studied how emotion can be detected using predictive neural networks in order to separate areas of interest for emotions represented by vowels, from regions of noise or pause between utterances. A Deep-Learn...
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this article used OpenCV (Open Source computer Vision Library) to preprocess images, and then used positioning methods and horizontal and vertical projection methods to accurately locate the key information to be reco...
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Object detection technology has been widely used in many real world applications. Withthe development of the deep learning method, the accuracy and speed of object detection method have been improved significantly, d...
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Object detection technology has been widely used in many real world applications. Withthe development of the deep learning method, the accuracy and speed of object detection method have been improved significantly, demonstrating great promises to increase the efficiency of security-related business activities. Nevertheless, the robustness of the existing object detection methods on security video datasets is still lacking. this could substantially reduce performance in complex application scenarios, such as changeable target size, target occlusion and bad weather. this cannot be solved perfectly by image-based object detection because a single image's information is limited. On the other hand, the video dataset consists of a series of still images of rich temporal and spatial information, which could be used as supplements for the detection methods. Based on this idea, this thesis proposes a method that solves the existing problems of the object detection method named local information aggregation and global information aggregation based on priori attribute information, and so as to aggregate features selectively by including more of the correlated feature information and less of the uncorrelated feature information. As such, the network could extract and learn more useful target features and abandon the interfered features. the accuracy of the proposed local global information aggregation methods could be improved by 0.9% and 1.1%, respectively compared with one of the most advanced video-based object detection methods MEGA. By adding both two modules, the mAP of the proposed method reaches 84.6% on the public dataset ImageNet VID, which is 1.7% higher than the mAP of MEGA. the proposed method also demonstrates potentials to detect occluded targets with high confidence.
the proceedings contain 102 papers. the topics discussed include: a vision-based method for human activity recognition using local binary pattern;DPRNN-FORMER: an efficient way to deal with blind source separation;dia...
ISBN:
(纸本)9798350330151
the proceedings contain 102 papers. the topics discussed include: a vision-based method for human activity recognition using local binary pattern;DPRNN-FORMER: an efficient way to deal with blind source separation;diagnosis of depression based on new features extractive from the frequency space of the EEG;spatio-temporal graph neural networks for accurate crime prediction;classification of benign and malignant tumors in digital breast tomosynthesis images using radiomic-based methods;intensity-image reconstruction using event camera data by changing in LSTM update;the Internet of things-enabled smart city: an in-depth review of its domains and applications;analysis of insect-plant interactions affected by mining operations, a graph mining approach;and leveraging the power of object detection models in identifying litter for a significant reduction in environmental pollution.
the time-sensitive Internet of things (IoT) applications within 5G and edge computing environments presents unique challenges in network resource management. Current systems struggle with efficiently managing the high...
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Reproducible wireless experiments pose a particular challenge due to their susceptibility to interference and changing channel conditions. Unlike most wired networks, they do not have dedicated connections or well-sha...
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ISBN:
(纸本)9798350388015;9798350388008
Reproducible wireless experiments pose a particular challenge due to their susceptibility to interference and changing channel conditions. Unlike most wired networks, they do not have dedicated connections or well-shared frequencies. this makes broadcast media such as wireless networks a challenge for reproducible experiments that are comparable to real-world scenarios. there are many attempts to approach these difficulties, either by simulation, emulation, or dedicated testbeds. All of them have certain strengths in specific applications, but also certain weaknesses - with respect to accuracy, flexibility, and cost. We therefore propose a combination of a physical link under a controlled environment, together with virtual wireless interfaces (VIFs) used to emulate arbitrary topologies. this allows us to make use of the real-world behavior of hardware with respect to timings such as media access while offering the flexibility of an emulated environment. By using containers for individual emulated nodes that use VIFs we can setup such topologies on a single host. In addition, measurement tools and applications can be run natively within this setup.
In this paper, we propose a novel decentralized learning algorithm over networks, termed as DLAGD, which combines the consensus mechanism with an auto-switchable local optimizer. Specifically, each node updates its lo...
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Emotion detection plays a vital role in understanding human behavior and enhancing human computer interaction. this study presents the development and evaluation of an Emotion Detection Tool utilizing machine learning...
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this paper is a research review that delves into the realm of machine learning techniques for risk management, focusing on the intricate interplay between wireless networks and the burgeoning paradigm of smart cities....
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ISBN:
(纸本)9798350385434;9798350385427
this paper is a research review that delves into the realm of machine learning techniques for risk management, focusing on the intricate interplay between wireless networks and the burgeoning paradigm of smart cities. As the digital ecosystem continues to expand, encompassing diverse domains such as mobile networks, vehicular communication, and energy-efficient protocols, the need for robust risk management strategies has become increasingly imperative.
Formalised libraries of combinatorial mathematics have rapidly expanded over the last five years, but few use one of the most important tools: probability. How can often intuitive probabilistic arguments on the existe...
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ISBN:
(纸本)9798400704888
Formalised libraries of combinatorial mathematics have rapidly expanded over the last five years, but few use one of the most important tools: probability. How can often intuitive probabilistic arguments on the existence of combinatorial structures, such as hypergraphs, be translated into a formal text? We present a modular framework using locales in Isabelle/HOL to formalise such probabilistic proofs, including the basic existence method and first formalisation of the Lovasz local lemma, a fundamental result in probability. the formalisation focuses on general, reusable formal probabilistic lemmas for combinatorial structures, and highlights several notable gaps in typical intuitive probabilistic reasoning on paper. the applicability of the techniques is demonstrated through the formalisation of several classic lemmas on the existence of hypergraphs with certain colourings.
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