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Functions of complex variables arise frequently in the formulation of sig - nal processing problems. The basic calculus rules on differentiation and integration for functions of complex variables resemble, but are not identical to, the rules of their real variable counterparts.
Industrial control systems (ICSs) manage and monitor critical civil or military infrastructure, such as water treatment facilities, power plants, electricity grids, transportation systems, oil and gas refineries, and health care.
In this column of IEEE Signal Processing Magazine, 46 IEEE Signal Processing Society (SPS) members are recognized as IEEE Fellows and award recipients are announced.
During the Christmas break, I had a mundane problem to solve. Most PCs today no longer come with disk drives. This was problematic for me since, like for many of you, my family videos are stored on CDs and DVDs.
Lecture Date: April 25-26, 2019
Chapter: Dallas
Chapter Chair: Issa Panahi
Topic: Robust and Practical Approaches to the
Cocktail Party Problem for Hearing Devices
Submission Deadline: March 25, 2019
Call for Proposals Document
May 20-24, 2019
Registration Deadline: April 30, 2019
Location: Lecce, Italy
Website
July 14-31, 2019
Registration Deadline: May 5, 2019
Location: Xi’an, China
Website
Submission Deadline: May 3, 2019
Call for Proposals Document
Title: Machine Learning/Speech research internship @ Seattle, WA
Time: Summer/Fall 2019
About You
A wiliness to be a better you on a day by day basis.
About Us:
We enable hundreds of millions of commercial and social interactions among our users, between consumers and merchants, and among businesses every day though speech.
What You’ll Do
Postdoctoral Research Grant (BPD) for the R&D Integrated Program “C4 – Centro de Competências em Cloud Computing”
Reference: “C4_MP_D1-b (En)”
A novel scheme of edge detection based on the physical law of diffusion is presented in this paper. Though the most current studies are using data based methods such as deep neural networks, these methods on machine learning need big data of labeled ground truth as well as a large amount of resources for training.
Retrieving specific persons with various types of queries, e.g., a set of attributes or a portrait photo has great application potential in large-scale intelligent surveillance systems. In this paper, we propose a richly annotated pedestrian (RAP) dataset which serves as a unified benchmark for both attribute-based and image-based person retrieval in real surveillance scenarios.
Image annotation aims to annotate a given image with a variable number of class labels corresponding to diverse visual concepts. In this paper, we address two main issues in large-scale image annotation: 1) how to learn a rich feature representation suitable for predicting a diverse set of visual concepts ranging from object, scene to abstract concept and 2) how to annotate an image with the optimal number of class labels.