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2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
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7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
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Autonomous Vehicles at the Intersection of Computer Vision, Machine Learning and Human Factors
About the project
Who we are looking for:
An experienced signal processing engineer who is creative, innovative, thrives on technical challenges, and is comfortable merging concepts from different technical disciplines.
Experience (required):
• 5 years of signal processing experience (analysis, modification, and synthesis)
• strong background emphasizing and detecting components in signals
• strong data analysis/data science abilities
• strong programming abilities
The Signal Acquisition, Modeling, Processing and Learning (SAMPL) lab headed by Prof. Yonina Eldar at the Weizmann Institute of Science is recruiting PhD, MSc and post-doctoral students for cutting-edge research applying signal processing and machine learning for communication and radar systems.
Candidates with strong algorithmic background are invited to send their CV and 3 recommendations.
OPTIMA group (https://optima.meduniwien.ac.at) is seeking an exceptionally motivated postdoc to strengthen our interdisciplinary team working on deep learning for medical image analysis. As part of our new initiative on Artificial Intelligence in Retina you will be leading exciting projects, at the interface of computer science and medicine.
June 29 - July 2, 2021
Location: Bristol, UK
June 28-30, 2021
Location: Lille, France
Lecture Date: December 14, 2020 (Online lecture)
Chapter: Singapore
Chapter Chair: Lokesh Bheema Thiagarajan
Topic: Privacy-Preserving Localization and Recognition of Human Activities
Inspired by the recent success of deep neural networks and the recent efforts to develop multi-layer dictionary models, we propose a Deep Analysis dictionary Model (DeepAM) which is optimized to address a specific regression task known as single image super-resolution. Contrary to other multi-layer dictionary models, our architecture contains
This paper is focused on simultaneous target detection and angle estimation with a multichannel phased array radar. Resorting to a linearized expression for the array steering vector around the beam pointing direction, the problem is formulated as a composite binary hypothesis test where the unknowns, under the alternative hypothesis, include the target directional cosines displacements with respect to the array nominal coarse pointing direction.
Decentralized detection is one of the key tasks that a wireless sensor network (WSN) is faced to accomplish. Among several decision criteria, the Rao test is able to cope with an unknown (but parametrically-specified) sensing model, while keeping computational simplicity. To this end, the Rao test is employed in this paper to fuse multivariate data measured by a set of sensor nodes, each observing the target (or the desired) event via a nonlinear mapping function.