2.1. Formulation of research questions. As our systematic review looks to explore the realm of FL and parameter aggregation, several crucial research questions (RQs) organically surface, steering the investigation towards a holistic grasp of FL (see Fig. 3).These RQs serve as a beacon, illuminating the review process and addressing the key facets of interest.
Our results show that, SwitchAgg can aggregate data at line rate and give a high data reduction ratio, which helps us cut down network traffic and alleviate pressure on server CPU. In the …
Finally, the experimental results on five public benchmark datasets show that the proposed network reaches a running speed of 125fps on a single GTX 1080Ti GPU for 352×352 images and uses only 3.68MB parameters to achieve an equivalent or even better performance than current state-of-the-art methods. ... IEEE Transactions on Image Processing.
Convolution Neural Network for Image Processing — Using Keras. A comprehensive guide towards working with CNN in Python. ... In other worlds think of it like a complicated process where the Neural Network or any machine learning algorithm has to work with three different data (R-G-B values in this case) to extract features of the images and ...
SwitchML is a co-design of in-switch processing with an end-host transport layer and ML frameworks. It leverages the following insights. First, aggregation involves a simple arithmetic …
In our study, we integrated various optical instruments using matlab to form a data acquisition system controlling the laser system, motorized translation stages, and image capturing and processing. A total of 40 different neural networks with varying hidden layer structures and training algorithms such as Levenberg–Marquardt (LM), 12 Bayesian regularization (BR), 13 …
In-network aggregation based routing protocols are divided to the following approaches: tree-based, cluster-based, multipath, and hybrid. Synopsis diffusion [2] is a general framework …
ip_rcv is the entry function for the IP network layer processing module, which first determines whether the packet needs to be discarded (the destination mac address is not the current NIC and the NIC is set to promiscuous mode), and if further processing is required calls the processing function in the NF_INET_PRE_ROUTING chain registered in ...
All circuits are synthesized in a 28nm commercial CMOS process with precision ranging from 2 to 8 bits. This work analyzes the impact of scalability and compares the different MAC units in terms of energy, throughput and area, aiming to understand the optimal architectures to reduce computation costs in neural-network processing.
Using the Neural network Image Processing Tool (hereafter, "the tool"), you can apply the following deep learning-based image processing to ... this tool's Digital Lens Optimizer processing to RAW images captured with lenses not supported by the tool will process the images using the normal Digital Lens Optimizer. Otherwise, diffraction is ...
1. In-network Aggregation: This is a general process of gathering and routing information through a multi-hop network. 2. Tree-based Approach: The tree based approach defines aggregation from constructing an aggregation tree. Tree structure is minimum spanning tree, sink node observe as a root and source node consider as a leaves.
A process network is determinate if its input/output behavior can be expressed as a function. ... Instead of processing an event for the whole process network at once, it may in some cases be possible to make the changes along with the 'information flow'. In particular, if the response of a network to an event is the forwarding of the event ...
This article focuses on the concept of Process-in-Network (PIN), which is defined as the possibility that the network processes information as it is being transmitted, and …
In this paper, we proposed an in-network data processing architecture to improve the energy efficiency and the scalability and the accuracy of sensor networks. We also adapted a data mining algorithm to process data for matching a specific event. The simulations show a reduction in energy consumption and an improvement in data accuracy.
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Besides, there also exists a dilution process of high-level features as they passed on the top-down pathway. To remedy these issues, we propose a novel network named GCPANet to effectively integrate low-level appearance features, high-level semantic features, and global context features through some progressive context-aware Feature Interweaved ...
Each network processing unit (NPU) has frame memory attached to it and this frame memory is where packet buffering is seen. The Trident -L and -B cards send a 50ms burst of traffic.The Trident -E card sends a maximum 150ms burst of traffic. ... As a suggested fix from c-nsp I've restarted ipv4_rib process and the FIB in LC was successfully ...
Abstract: In-Network Processing (INP) is an effective way to aggregate and process data from different sources and forward the aggregated data to other nodes for further processing until it reaches the end user. There is a trade-off between energy consumption for processing data and communication energy spent on transferring the data. An essential requirement in the INP …
Each sensor node computes a partial result of the digest function and passes that result to other neighboring sensor nodes. In-network aggregation has better energy-efficiency characteristics, communication overhead is less and the computation is …
Distributed Optimization Framework for In-Network Data Processing. Abstract: In-Network Processing (INP) is an effective way to aggregate and process data from different sources …
Among the available aggregation methods, in-network processing plays a major role to reduce the amount of data to be transmitted in the network. This article analyzes the …
The collection process requires dynein motors that transport cellular aggregates along the microtubule network to the microtubule organization center (MTOC), where the aggregates are packed into aggresomes (Kopito, 2000). The synthesis of aggresomes is a response to proteostatic stress, and is functionally analogous to a "triage" center ...
The unceasing development of Artificial Intelligence (AI) and Machine Learning (ML) techniques is growing with privacy problems related to the training data. A relatively recent approach to partially cope with such concerns is Federated Learning (FL), a technique in which only the parameters of the trained neural network models are transferred rather than data. Despite the benefits that …
Abstract: Emerging Wireless Sensor Network (WSN) applications demand considerable computation capacity for in-network processing. To achieve the required processing capacity, cross-layer collaborative in-network processing among sensors emerges as a promising solution: Sensors do not only process information at the application layer, but also …
In a Processing Network (PN) simulation, often called process-oriented simulation, processing objects (representing, e.g., customers or manufacturing parts) enter a system via arrival events at an entry node and then flow along a chain of processing nodes (representing, e.g., sevice desks or manufacturing machines) where they are subject to processing activities before they leave …
Besides, there also exists a dilution process of high-level features as they passed on the top-down pathway. To remedy these issues, we propose a novel network named GCPANet to effectively integrate low-level appearance features, high-level semantic features, and global context features through some progressive context-aware Feature Interweaved ...
Network Processor: A network processor (NPU) is an integrated circuit that is a programmable software device used as a network architecture component inside a network application domain. A network processor in a network is analogous to central processing unit in a computer or similar device. The replacement of analogous signals to packet data ...
HOLODEC, an airborne cloud particle imager, captures holographic images of a fixed volume of cloud to characterize the types and sizes of cloud particles, such as water droplets and ice crystals. Cloud particle properties include position, diameter, and shape. We present a hologram processing algorithm, HolodecML, that utilizes a neural segmentation model, …
Most of the research on salient object detection pursues performance but ignores efficiency, resulting in poor practicability. In this paper, we propose a lightweight SOD solution, named GIPANet, which better alleviates the contradiction between model size and performance. Firstly, to solve the problems of shallow depth and insufficient information extraction in …
This paper aims at contributing to the ongoing debate on how to bring programmability of stateful packet processing tasks inside the network switches, while retaining platform independency. Our proposed approach, named "Open Packet Processor" (OPP), shows the viability (via an hardware prototype relying on commodity HW technologies and operating …
Data Aggregation Process. Aggregation of data usually involves a series of processes that you can follow to maximize the quality of data generated for cleaning, transformation, and analysis: These processes include: I. Collection. Gathering related data from various sources, like databases, websites, social media, and sensors.
This document proposes extensions for IGP to order to advertise the aggregate header limit of a node or a link on a node to for efficient packet processing. Aggregate …
In this work, authors introduce an innovative loopback strategy for In-Vehicle Network (IVN) processing in automotive gateway (GW) Network on Chip. The new proposed architecture is fully HW centric, and allows performing any IVN processing algorithms without intervention from the CPU. ... The process may takea few minutes but once it finishes a ...
aggeregation process in network processing T13:05:29+00:00 ProcessinNetwork: a comprehensive network . This article focuses on the concept of ProcessinNetwork (PIN), which is defined as the possibility that the network processes information as it is being transmitted, and introduces a more comprehensive approach than current network ...
