Results 11 to 20 of about 28,939,072 (320)
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing [PDF]
IEEE Journal on Selected Topics in Signal Processing, 2021 Self-supervised learning (SSL) achieves great success in speech recognition, while limited exploration has been attempted for other speech processing tasks.
Sanyuan Chen +16 more
semanticscholar +1 more source
In-datacenter performance analysis of a tensor processing unit [PDF]
International Symposium on Computer Architecture, 2017 Many architects believe that major improvements in cost-energy-performance must now come from domain-specific hardware. This paper evaluates a custom ASIC-called a Tensor Processing Unit (TPU)-deployed in datacenters since 2015 that accelerates the ...
Norman P. Jouppi +75 more
semanticscholar +1 more source
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing [PDF]
Conference on Empirical Methods in Natural Language Processing, 2018 This paper describes SentencePiece, a language-independent subword tokenizer and detokenizer designed for Neural-based text processing, including Neural Machine Translation. It provides open-source C++ and Python implementations for subword units.
Taku Kudo, John Richardson
semanticscholar +1 more source
Efficient Processing of Deep Neural Networks: A Tutorial and Survey [PDF]
Proceedings of the IEEE, 2017 Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI) applications including computer vision, speech recognition, and robotics.
V. Sze +3 more
semanticscholar +1 more source
Is ChatGPT a General-Purpose Natural Language Processing Task Solver? [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot -- i.e., without adaptation on downstream data.
Chengwei Qin +5 more
semanticscholar +1 more source
8th International Multitopic Conference, 2004. Proceedings of INMIC 2004., 2018 This paper provides a review of the Teager–Kaiser (TK) energy operator and its extensions for signals and images processing. This class of operators possesses simplicity and good time-resolution and is very efficient in instantaneously estimating AM–FM ...
T. Cavicchi, Umberto Spagnolini
semanticscholar +1 more source
Magnetic Resonance Materials in Physics, Biology and Medicine, 2020 Image processing entails altering an image's composition to enhance its graphical content for human interpretation and autonomous machine perception. Digital image processing is a subset of the electronic domain in which an image is transformed into a ...
Scott Weiss
semanticscholar +1 more source
Pre-Trained Image Processing Transformer [PDF]
Computer Vision and Pattern Recognition, 2020 As the computing power of modern hardware is increasing strongly, pre-trained deep learning models (e.g., BERT, GPT-3) learned on large-scale datasets have shown their effectiveness over conventional methods. The big progress is mainly contributed to the
Hanting Chen +9 more
semanticscholar +1 more source
Thought/ visual processing: ctrl + x, y, z, v [PDF]
, 2012 With this text I wish to revisit a long-standing preoccupation of mine which addresses the extent to which the digital medium may have brought about a paradigm shift in creative process; one which has been effectuated through a conversion of the creative
Ayiter, Elif
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An AER Spike-Processing Filter Simulator and Automatic VHDL Generator Based on Cellular Automata [PDF]
, 2011 Spike-based systems are neuro-inspired circuits implementations traditionally used for sensory systems or sensor signal processing. Address-Event- Representation (AER) is a neuromorphic communication protocol for transferring asynchronous events ...
Civit Balcells, Antón +5 more
core +1 more source