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PhD Thesis in Medical Image Processing (Matlab Code)
The Stanford Compression Workshop was held virtually on February 25th and 26th, The Workshop is a gathering of people from academia and industry interested in new and improved ways to model, represent, store, compress, query, process, communicate and protect the data the world is amassing. It encompasses diverse areas including genomic data compression, quantum information, video compression with an emphasis on perceptual quality, DNA-based data storage, neuroscience, databases, computation on compressed and distributed data, virtual theater technologies, compression of neural network models, and the use of neural networks for data compression.
The workshop consists of talks and panels comprising students, academia, and industry participants, as well as a poster session. The schedule and other information is available below. The poster session will also be virtual and will be organized on gather.
We are excited to announce a best poster prize Netflix vouchers! Questions will be entertained at the end of the talks and throughout the panels, phd thesis on video compression. Gather town link will be provided here 30 minutes before the poster session on Thursday and before the social hangout on Friday. We have created a README document with instructions on navigating the interface. Please use Chrome browser to avoid technical issues. Join Slack workspace for informal networking and for technical discussions.
Registered participants will receive an invite, let the organizers know if you don't. We show how an image can be casted onto a real, entangled state, and then processed for compression.
We also show a quantum compression scheme for a quantum state, based on variational quantum autoencoders. Bio: José Ignacio Latorre is the Director of the Center for Quantum Technologies in Singapore, phd thesis on video compression, and the Chief Scientist at the Quantum Research Centre of the Technology Innovation Institute in Abu Dhabi.
He has worked in quantum field theory, renormalization group, quantum information and computation. Abstract: Accessibility of cheap sequencing technologies allowed comparative genomics to extend its field of interests from viruses in the s to humans in the s. Nowadays, the largest sequencing projects cover tens or even hundreds of thousands of individuals. It seems obvious that in the near future we will see collections of millions of human genomes.
Genome collections are usually stored in the Variant Call Format VCF files. Such files are usually huge and require compression. In the talk, I will discuss modern attempts to reduce the space necessary for VCF files. Moreover, I will show how a lot of queries can be answered without decompressing the VCF files. Bio: Sebastian Deorowicz is a Phd thesis on video compression and Head of Algorithmics and Software Department at Silesian University of Technology, Poland.
He completed his PhD in in Computer Science. In he moved to bioinformatics. This includes compression of sequencing data in FASTQ format as well as genome collections in VCF or FASTA formats for efficient storage and transfer. The works include also development of compressed data structures allowing fast queries of various types to compressed genome collections. The group develops also tools for analysis of genomic data, e.
Other work focuses on multiple sequence alignments of huge protein families. The main goal phd thesis on video compression the group is to offer high-performant implementations able to work both on the server and workstation platforms.
Abstract: Sequencing data are often summarized at different annotation levels for further analysis, generally using the general feature format GFF or its descendants, gene transfer format GTF and GFF3. Existing utilities for accessing these files, like gffutils and gffread, do not focus on reducing the storage space, significantly increasing it in some cases. We propose GPress, a framework for querying GFF files in a compressed form.
GPress can also incorporate and compress expression files from both bulk and single-cell RNA-Seq experiments, supporting simultaneous queries on both the GFF and expression files, phd thesis on video compression. In brief, phd thesis on video compression, GPress applies transformations to the data which are then compressed with the general lossless compressor BSC. To support queries, GPress compresses the data in blocks and creates several index tables for fast retrieval.
In contrast, gffutils provides faster retrieval but doubles the size of the GFF files. Bio: Dr. Ochoa graduated with B. and M.
degrees in Electrical Engineering from the University of Navarra, Spain, in She then went to Stanford, where she obtained a MS and a PhD in the Electrical Engineering Department, in andrespectively.
During her time at Stanford Dr, phd thesis on video compression. Ochoa performed internships as a software engineering at Google, CA and at Genapsys, CA.
After obtaining the PhD, Dr. Ochoa joined the faculty at the Electrical and Computing Engineering department at the University of Illinois at Urbana-Champaign UIUCas an assistant professor, in January After three years at UIUC, Dr.
Ochoa joined the faculty at Tecnun as a collaborator professor in January She still holds an adjunct faculty position at UIUC and continues advising her PhD students. Her research interests include computational biology, data compression, bioinformatics, information theory and coding, machine learning, communications, and signal processing.
In particular, her research focuses on the development of computational methods tailored to omics data, to aid the storage, handling, and analysis of these data. She has developed several compression algorithms for genomic, methylation and mass spectrometry data that are currently the state-of-the-art, as well as novel computational tools to improve the genomic analysis pipeline, such as a novel variant filtering tool based on ensemble methods.
Ochoa is recipient of the Stanford Graduate Fellowship, La Caixa Graduate Fellowship, and an award for excellence from the Basque Government, phd thesis on video compression. She has also been recently awarded the MIT Innovators under 35 award, the Gipuzkoa Fellows, and a Ramon y Cajal grant. Abstract: We define the problem, highlight some differences between the quantum and the classical settings, summarize major results, and discuss a few phd thesis on video compression developments.
Bio: Debbie Leung has been a faculty member at the Institute for Quantum Computing and the Department of Combinatorics and Optimization phd thesis on video compression the University of Waterloo since She works on quantum information theory, including the study of quantum channel capacities, quantum correlations, and quantum error correction. She obtained her PhD in Physics from Stanford University, and worked as a postdoctoral fellow at Caltech and IBM TJ Watson Research Center.
Abstract: In recent work, we have extended the concept of learnable video precoding rate-aware neural-network processing prior to encoding to deep perceptual optimization DPO. Our framework phd thesis on video compression a pixel-to-pixel convolutional neural network that is trained based on the virtualization of core encoding blocks block transform, quantization, block-based prediction and multiple loss functions representing elements of rate, distortion and perceptual quality achieved by the virtual encoder.
We shall also explore some interesting complexity vs. Bjontegaard delta-rate BD-rate trade-offs enabled by our proposal and make some visual comparisons showing the visual quality difference corresponding to the reported BD-rate gains. Some suggestions for further extensions will be outlined.
Bio: Yiannis Andreopoulos is Technical Director at iSIZE, a London-based AI company optimizing video delivery. He is also Professor of Data and Signal Processing Systems at University College London UCL. His research interests are in video signal processing, machine learning and high-performance computing. He has published extensively in these areas and his work has been recognised by best paper awards and a Senior Research Fellowship from the Royal Academy of Engineering and the Leverhulme Trust, phd thesis on video compression.
Abstract: In the age of exponential growth of video conferencing and video on demand services, video compression has become more and more important. In the past few years, there has been a significant amount of progress in designing video compression techniques using machine learning to augment or replace the traditional video codecs. In this talk, I will discuss some of the key ideas shaping the next generation of learned video codecs, phd thesis on video compression, and how they improve upon some of the shortcomings of traditional codecs.
In spite of the impressive strides, significant challenges remain in making the learned video codecs a reality. I will discuss some of the key challenges, phd thesis on video compression, and how we at WaveOne are working towards overcoming them. Bio: Kedar is a research scientist at WaveOne Inc. He received his Ph. from Stanford University inwhere he specialized in the field of data compression and information theory.
He holds a B. Tech in Electrical Engineering Indian Institute of Technology, Bombay, and a M. from Stanford University. Kedar is the recipient of the Numerical Technologies Founders Prize at Phd thesis on video compression, and the Qualcomm Innovation Fellowship.
Abstract: At Netflix, we strive to serve our members the best viewing experience possible. This means that we need to spend bits in a way that maximizes the perceptual quality of each video, on each device, in each streaming session. Naturally, such optimization requires a reliable way to quantify the observed quality.
This talk will cover our efforts towards developing more accurate methods of measuring the subjectively perceived video quality under different viewing conditions, as well as the design of algorithms capable of estimating the quality automatically.
Bio: Christos G. Bampis is currently working as an engineer within the Encoding Technologies team at Netflix, focusing on the research and productization of video quality algorithms at scale. Before that, he received a Ph. degree in Electrical and Computer Engineering from the University of Texas at Austin in the US and a Diploma degree from the National Technical University of Athens in Greece. In his free time, phd thesis on video compression, he likes reading and writing poetry, practicing martial arts, and traveling.
He spends most of his days trying to figure out how to improve objective video quality metrics. He holds a double Ph. degree in Computer Science and Radioelectronics from the University of Nantes, France, and Czech Technical University in Prague, Czech Republic, respectively. Abstract: COVID has made video phd thesis on video compression one of the most important modes of information exchange.
While extensive research has been conducted on the optimization of the video streaming pipeline, in particular the development of novel video codecs, further improvement in the video quality and latency is required, especially under poor network conditions. This paper proposes an alternative to the conventional codec through the implementation of a keypoint-centric encoder relying on the transmission of keypoint information from within a video feed. The decoder uses the streamed keypoints to generate a reconstruction preserving the semantic features in the input feed.
Focusing on video calling applications, we detect and transmit the body pose and face mesh information through the network, which are displayed at the receiver in the form of animated puppets. Using efficient pose and face mesh detection in conjunction with skeleton-based animation, we demonstrate a prototype requiring lower than 35 kbps bandwidth, an order of phd thesis on video compression reduction over typical video calling systems.
ICLR 2021 - Conditional Coding for Flexible Learned Video Compression
, time: 4:42Lossless Video Codecs « Kostya's Boring Codec World
PhD Thesis in Medical Image Processing PhD Thesis in Medical Image Processing is prime idea to give quality of project and thesis for you. We have + professionals those who dedicated themself in research to serving you. So We have developed more than + projects for current researchers and young minds students to enhance their future in the area of research The focus of this thesis is the design of rate-control (RC) algorithms for constant quality (CQ) video encoding and transcoding, where CQ is measured by the variance of quality in PSNR (peak signal-to-noise ratio). By modeling DCT coefficients as having Laplacian distributions, Laplacian rate/models are developed for MPEG-4 encoding and transcoding By making an order beforehand, not only do you save money but Phd Thesis On Video Compression also let your dissertation writer alter the paper as many times as you need within the day free revision period. If you have a complicated task at hand, the best solution is to pick a 3+ day turnaround
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