The aim of this paper is to present a new method for skin tumor segmentation in the 3D ultrasound images. We consider a variational formulation, the energy of which combines a diffuse interface phase field model (regularization term) and a log-likelihood computed using nonparametric estimates (data attachment term).
What sparked your interest in speech and language processing?
Early on, I was amazed by the ambiguity of natural language, that so many sentences could in fact be parsed and understood in different ways, and yet we can often times easily communicate with each other and interpret what we hear or read with the intended semantics. Then I found out in college that speech and natural language is actually quite an active area for computer science.
This year was one of the largest ICASSP conferences that I have attended with more than 3,000 participants. During opening remarks, SPS president, Ali H. Sayed announced that the membership fees for students has been set to $1, there will be an open access journal for signal processing, IEEE SPS formal policy statement for commitment to diversity, and initiating an E-learning center which are great steps forward to create an open society.
Predicting articulatory movements from audio or text has diverse applications, such as speech visualization. Various approaches have been proposed to solve the acoustic-articulatory mapping problem. However, their precision is not high enough with only acoustic features available. Recently, deep neural network (DNN) has brought tremendous success in various fields, like speech recognition and image processing.
With the development of video coding technology, high-efficiency video coding (HEVC) has become a promising alternative, compared with the previous coding standards, for example, H.264. In general, H.264 to HEVC transcoding can be accomplished by fully H.264 decoding and fully HEVC encoding, which suffers from considerable time consumption on the brute-force search of the HEVC coding tree unit (CTU) partition for rate-distortion optimization (RDO).
The saliency detection technologies are very useful to analyze and extract important information from given multimedia data, and have already been extensively used in many multimedia applications. Past studies have revealed that utilizing the global cues is effective in saliency detection. Nevertheless, most of prior works mainly considered the single-scale segmentation when the global cues are employed. In this paper, we attempt to incorporate the multi-scale global cues for saliency detection problem.
IEEE Signal Processing Society (SPS) President, Ali H. Sayed, is seeking nominations for the positions of Chair and Vice Chair of the IEEE SPS Fellow Evaluation Committee. The term of appointment for each position is one year, renewable (1 January 2020-31 December 2020).
Amazon AI has open positions in Palo Alto, California, for applied scientists (both interns and full time)
in all areas of human language technology, with special focus on Deep Learning (DL) models for
speech recognition, machine translation and text-to-speech.
Interested candidates are invited to contact me or to submit their application online at
https://www.amazon.jobs/en/jobs/803520/applied-scientist
Marcello Federico
marcfede@amazon.com
Radar was developed during World War II for defense and security applications, and it was initially used for detecting aircrafts and missiles, replacing short range and narrow field-of-view acoustic devices.