The era of smart connectivity spawned by the Internet of Things (IoT) has made the need to achieve environmental perception and understanding of different scenarios increasingly urgent. Among the many scenarios, indoo...
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The era of smart connectivity spawned by the Internet of Things (IoT) has made the need to achieve environmental perception and understanding of different scenarios increasingly urgent. Among the many scenarios, indoor scene classification has attracted much attention because of its its relevance to the daily lives of people, ranging from comfort regulation in living spaces to the optimal allocation of resources in offices, and a variety of approaches for this task have emerged. However, increasing accuracy remains a crucial objective due to the complexity and disorder of indoor scenes. Therefore, we propose a feature contrast difference and enhanced network for RGB-D indoor scene classification, FCDENet. First, the RGB and Depth images express different information. Therefore, we built a feature contrast difference module for the first two low-level features to extend the receptive fields of the different features, utilizing differential contrast to complement each other. Second, the high-level feature semantic information is abstract. Therefore, we introduced information cluster blocks, which are used to aggregate feature points with similar attributes into compact clusters after being parsed by an initial frequency transform, enabling instantiated representations of the semantic information. Finally, to further enhance the integrated features, we introduced a wavelet transform block in the cross-layer decoding process. In contrast to conventional decoding methods, we employed a wavelet transform for initial denoising cross-layer features and used multiple pooling structures to supplement local information, gradually weighting to achieve higher prediction accuracy. Extensive experiments on two typical indoor datasets, NYUDv2 and SUN RGB-D, show that our results exhibit excellent performance. In addition, to better demonstrate the reliability of the method, we conducted generalizability experiments on other datasets, and the proposed method provides a robust soluti
The increaing significance of plant life and botanical expertise extends beyond mere visual appreciation. With the growing interest in sustainable living and alternative remedies, there is a pressing demand for easily...
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A novel quantum search algorithm tailored for continuous optimization and spectral problems was proposed recently by a research team from the University of Electronic science and Technology of China to broaden quantum...
A novel quantum search algorithm tailored for continuous optimization and spectral problems was proposed recently by a research team from the University of Electronic science and Technology of China to broaden quantum computation frontiers and enrich its application *** computing has traditionally excelled at tackling discrete search challenges, but many important applications from large-scale optimization to advanced physics simulations necessitate searching through continuous domains.
Detecting sarcasm in social media presents challenges in natural language processing (NLP) due to the informal language, contextual complexities, and nuanced expression of sentiment. Integrating sentiment analysis (SA...
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The Internet ofThings(IoT)and edge computing have substantially contributed to the development and growth of smart *** handled time-constrained services and mobile devices to capture the observing environment for surv...
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The Internet ofThings(IoT)and edge computing have substantially contributed to the development and growth of smart *** handled time-constrained services and mobile devices to capture the observing environment for surveillance *** systems are composed of wireless cameras,digital devices,and tiny sensors to facilitate the operations of crucial healthcare ***,many interactive applications have been proposed,including integrating intelligent systems to handle data processing and enable dynamic communication functionalities for crucial IoT ***,most solutions lack optimizing relayingmethods and impose excessive overheads for maintaining devices’***,data integrity and trust are another vital consideration for nextgeneration *** research proposed a load-balanced trusted surveillance routing model with collaborative decisions at network edges to enhance energymanagement and resource *** leverages graph-based optimization to enable reliable analysis of decision-making ***,mobile devices integratewith the proposed model to sustain trusted routes with lightweight privacy-preserving and *** proposed model analyzed its performance results in a simulation-based environment and illustrated an exceptional improvement in packet loss ratio,energy consumption,detection anomaly,and blockchain overhead than related solutions.
作者:
Du, AnJia, JieChen, JianWang, XingweiHuang, MingNortheastern University
School of Computer Science and Engineering Engineering Research Center of Security Technology of Complex Network System Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Northeastern University
School of Computer Science and Engineering Shenyang110819 China
Mobile edge computing (MEC) integrated with Network Functions Virtualization (NFV) helps run a wide range of services implemented by Virtual Network Functions (VNFs) deployed at MEC networks. This emerging paradigm of...
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The process of converting natural language requirements and visual models into executable software code remains an ongoing challenge in software engineering. We developed an intelligent system that adopts Natural Lang...
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Given a graph G=(V,E) and a set T={(si,ti):1≤i≤k}⊆V×V of k pairs, the k-Vertex-Disjoint-Paths (resp. k-Edge-Disjoint-Paths) problem asks to determine whether there exist k pairwise vertex-disjoint (resp. e...
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ISBN:
(纸本)9783031813955
Given a graph G=(V,E) and a set T={(si,ti):1≤i≤k}⊆V×V of k pairs, the k-Vertex-Disjoint-Paths (resp. k-Edge-Disjoint-Paths) problem asks to determine whether there exist k pairwise vertex-disjoint (resp. edge-disjoint) paths P1,P2,…,Pk in G such that, for each 1≤i≤k, Pi connects si to ti. Both the edge-disjoint and vertex-disjoint versions in undirected graphs are famously known to be FPT (parameterized by k) due to the Graph Minor Theory of Robertson and Seymour. Eilam-Tzoreff [DAM ‘98] introduced a variant, known as the k-Disjoint-Shortest-Paths problem, where each path is further required to be a shortest path connecting its pair. They showed that the k-Disjoint-Shortest-Paths problem is NP-complete on both directed and undirected graphs;this holds even if the graphs are planar and have unit edge lengths. We focus on four versions of the problem, corresponding to considering edge/vertex disjointness, and to considering directed/undirected graphs. Building on the reduction of Chitnis [SIDMA ’23] for k-Edge-Disjoint-Paths on planar DAGs, we obtain the following inapproximability lower bound for each of the four versions of k-Disjoint-Shortest-Paths on n-vertex graphs:Under the gap version of the Exponential Time Hypothesis (Gap-ETH), there exists a constant δ>0 such that for any constant 0δ·k time. Under the gap version of the Exponential Time Hypothesis (Gap-ETH), there exists a constant δ>0 such that for any constant 0δ·k time. We provide a single, unified framework to obtain lower bounds for each of the four versions of k-Disjoint-Shortest-Paths. We are able to further strengthen our results by restricting the structure of the input graphs in the lower bound constructions as follows:Directed: The inapproximability lower bound for edge-disjoint (resp. vertex-disjoint) paths holds even if the input graph is a planar (resp. 1-planar) DAG with max in-degree and max out-degree at most ***: The inapproximability lower bound for edge-disjoint (resp. vertex-dis
Recent model recovery methods in federated unlearning (FUL) either rely on additional communication with the remaining clients or require large amounts of high-quality data from the server for training, overlooking sc...
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The current research work proposes a difficultydriven comparison of three most visited automobile websites namely the Automobile Site1, Automobile Site2, Automobile Site3 on parameters including performance, Search en...
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