https://cis.temple.edu/~tug29203/teaching/fall2018-3329/lectures/ch3-1.ppt
Transport Layer 3-* Chapter 3: Transport Layer our goals: understand principles behind transport layer services: multiplexing, demultiplexing reliable data transfer flow control congestion control learn about Internet transport layer protocols: UDP: connectionless transport TCP: connection-oriented reliable transport TCP congestion control Transport Layer 3-* Chapter 3 outline 3.1 transport ...
https://cis-linux1.temple.edu/~jiewu/research/publications/Publication_files/ICPADS2024.pdf
Abstract—Federated Learning (FL) is an emerging privacy-preserving distributed machine learning paradigm that enables numerous clients to collaboratively train a global model without transmitting private datasets to the FL server. Unlike most existing research, this paper introduces a Data-Driven FL system in Unmanned Aerial Vehicle (UAV) networks, named DDFL, which features an innovative ...
https://www.fox.temple.edu/sites/fox/files/documents/CVs/xueming-luo-cv.pdf
Bio: Xueming Luo is the Charles Gilliland Distinguished Chair Professor of Marketing, Professor of Strategy, and Professor of MIS, and Founder/ Director of the Global Institute for Artificial Intelligence & Business Analytics in the Fox School of Business at Temple University. He is an interdisciplinary thought-leader in leveraging AI/ML algorithms, text/audio/image/video big data ...
https://cis.temple.edu/~latecki/Courses/CIS2033-Spring13/Modern_intro_probability_statistics_Dekking05.pdf
A modern introduction to probability and statistics. — (Springer texts in statistics) 1. Probabilities 2. Mathematical statistics I. Dekking, F. M.
https://cis.temple.edu/~latecki/Papers/JoPanECAI2024.pdf
Addressing these gaps, we introduce the FlowLearn Dataset1, which includes both scientific and simulated flowcharts. The scien-tific subset features 3,858 flowcharts sourced from scientific liter-ature, annotated with captions (median length of 25 words) and in-figure text. The simulated subset consists of 10,000 flowcharts gener-ated from Mermaid code. This simulated subset enhances the ...
https://cis.temple.edu/~latecki/Papers/ICIP2019.pdf
ABSTRACT The extensive computational burden limits the usage of CNNs in mobile devices for dense estimation tasks. In this paper, we present a lightweight network to address this prob-lem, namely LEDNet, which employs an asymmetric encoder-decoder architecture for the task of real-time semantic seg-mentation. More specifically, the encoder adopts a ResNet as backbone network, where two new ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/WENJUNJIANG2021TWeb.pdf
In online systems, including e-commerce platforms, many users resort to the reviews or comments generated by previous consumers for decision making, while their time is limited to deal with many reviews. Therefore, a review summary, which contains all important features in user-generated reviews, is expected. In this paper, we study “how to generate a comprehensive review summary from a ...
https://cis.temple.edu/~latecki/Papers/Quan_DRBANET_ICIP_2022.pdf
ABSTRACT Due to the powerful ability to encode image details and semantics, many lightweight dual-resolution networks have been proposed in recent years. However, most of them ignore the benefit of boundary information. This paper introduces a lightweight dual-resolution network, called DRBANet, aim-ing to refine semantic segmentation results with the aid of boundary information. DRBANet also ...