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Section: Publications & Resources

Ramalingam Chellappa Receives IEEE Jack S. Kilby Signal Processing Medal . IEEE Life Fellow Ramalingam Chellappa has received this year’s IEEE Jack S. Kilby Signal Processing Medal "for contributions to image and video processing, especially applications to face recognition." 

Section: Events

Submission Deadline: August 30, 2020 Call for Proposals Document

Open rank position in machine learning for medical image and signal processing

Section: Publications & Resources

Large-scale antenna arrays, also known as massive MIMO, are key enablers for 5G and beyond networks, which, however, bring tremendous pressures on hardware cost and energy consumption. 

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Deep learning methods haverevolutionized speech recognition, image recognition, and natural language processing since 2010. Each of these tasks involves a single modality in their input signals. However, many applications in the artificial intelligence field involve multiple modalities.

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Solving visual question answering (VQA) task requires recognizing many diverse visual concepts as the answer. These visual concepts contain rich structural semantic meanings, e.g., some concepts in VQA are highly related (e.g., red & blue), some of them are less relevant (e.g., red & standing).

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

We consider the problem of reliable information propagation in the brain using biologically realistic models of spiking neurons. Biological neurons use action potentials, or spikes, to encode information. Information can be encoded by the rate of asynchronous spikes or by the (precise) timing of synchronous spikes. Reliable propagation of synchronous spikes is well understood in neuroscience and is relatively easy to implement by biologically-realistic models of neurons. 

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Visual food recognition on mobile devices has attracted increasing attention in recent years due to its roles in individual diet monitoring and social health management and analysis. Existing visual food recognition approaches usually use large server-based networks to achieve high accuracy. 

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

This paper presents a novel approach for accurate barcodes detection in real and challenging environments using compact deep neural networks. Our approach is based on Convolutional Neural Network ( CNN ) and neural network compression, which can detect the four vertexes coordinates of a barcode accurately and quickly. Our approach consists of four stages: ( i ) feature extraction by a base network, ( ii ) region proposal network ( RPN ) training, ( iii ) barcode classification and coordinates regression, and ( iv ) weights pruning and recoding.

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Previous research methods on wake-up word detection (WWD) have been proposed with focus on finding a decent word representation that can well express the characteristics of a word. However, there are various obstacles such as noise and reverberation which make it difficult in real-world environments where WWD works.