Results 31 to 40 of about 1,645,972 (339)
Nature, 2020 The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms ...
Federico Abascal +256 more
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CE-Net: Context Encoder Network for 2D Medical Image Segmentation [PDF]
IEEE Transactions on Medical Imaging, 2019 Medical image segmentation is an important step in medical image analysis. With the rapid development of a convolutional neural network in image processing, deep learning has been used for medical image segmentation, such as optic disc segmentation ...
Zaiwang Gu +8 more
semanticscholar +1 more source
Connecting Speech Encoder and Large Language Model for ASR [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023 The impressive capability and versatility of large language models (LLMs) have aroused increasing attention in automatic speech recognition (ASR), with several pioneering studies attempting to build integrated ASR models by connecting a speech encoder ...
Wenyi Yu +8 more
semanticscholar +1 more source
Nature Communications, 2021 Recent advances in spatially resolved transcriptomics have enabled comprehensive measurements of gene expression patterns while retaining the spatial context of the tissue microenvironment.
Kangning Dong, Shihua Zhang
semanticscholar +1 more source
ACM Computing Surveys, 2017 Many proofs in discrete mathematics and theoretical computer science are based on the probabilistic method. To prove the existence of a good object, we pick a random object and show that it is bad with low probability. This method is effective, but the underlying probabilistic machinery can be daunting.
Pat Morin, Wolfgang Mulzer, Tommy Reddad
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TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2020 We introduce a self-supervised speech pre-training method called TERA, which stands for Transformer Encoder Representations from Alteration. Recent approaches often learn by using a single auxiliary task like contrastive prediction, autoregressive ...
Andy T. Liu, Shang-Wen Li, Hung-yi Lee
semanticscholar +1 more source
Lite DETR : An Interleaved Multi-Scale Encoder for Efficient DETR [PDF]
Computer Vision and Pattern Recognition, 2023 Recent DEtection TRansformer-based (DETR) models have obtained remarkable performance. Its success cannot be achieved without the re-introduction of multi-scale feature fusion in the encoder.
Feng Li +6 more
semanticscholar +1 more source
AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder [PDF]
British Machine Vision Conference, 2023 The recently introduced Segment Anything Model (SAM) combines a clever architecture and large quantities of training data to obtain remarkable image segmentation capabilities.
Tal Shaharabany +3 more
semanticscholar +1 more source
Examples of minimal-memory, non-catastrophic quantum convolutional encoders [PDF]
, 2011 One of the most important open questions in the theory of quantum convolutional coding is to determine a minimal-memory, non-catastrophic, polynomial-depth convolutional encoder for an arbitrary quantum convolutional code.
Hosseini-Khayat, Saied +2 more
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Symbol positions‐based Slepian–Wolf coding with application to distributed video coding
IET Image Processing, 2020 In this study, the authors will show that coding the positions of the symbols, instead of their values, can be a good way to implement efficient Slepian–Wolf (SW) coding and can reduce the complexity of both the encoder and the decoder.
Said Benierbah, Mohammed Khamadja
doaj +1 more source