Results 71 to 80 of about 9,899,096 (370)
SIGGRAPH Asia 2019 Courses, 2018 Concepts, terminology, structures, no math, no code. Free open-source libraries do the hard work. My background: consultant, writer, director, etc.
Polson, Nicholas G., Sokolov, Vadim O.
+7 more sources
Quantum Information and Computation, 2016 In recent years, deep learning has had a profound impact on machine learning and artificial intelligence. At the same time, algorithms for quantum computers have been shown to efficiently solve some problems that are intractable on conventional, classical computers.
Ashish Kapoor +2 more
openaire +3 more sources
The Programming Historian, 2022 This is the first of a two-part lesson introducing deep learning based computer vision methods for humanities research. Using a dataset of historical newspaper advertisements and the fastai Python library, the lesson walks through the pipeline of ...
Daniel van Strien +4 more
doaj +1 more source
, 2017 Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks. These methods have arguably had their strongest impact on tasks such as image and audio processing - data ...
Aimone, James B. +8 more
core +1 more source
The Programming Historian, 2022 This is the second of a two-part lesson introducing deep learning based computer vision methods for humanities research. This lesson digs deeper into the details of training a deep learning based computer vision model.
Daniel van Strien +4 more
doaj +1 more source
Deep High-Resolution Representation Learning for Human Pose Estimation [PDF]
Computer Vision and Pattern Recognition, 2019 In this paper, we are interested in the human pose estimation problem with a focus on learning reliable high-resolution representations. Most existing methods recover high-resolution representations from low-resolution representations produced by a high ...
Ke Sun +3 more
semanticscholar +1 more source
Performance Evaluation of Deep Learning Tools in Docker Containers
, 2017 With the success of deep learning techniques in a broad range of application domains, many deep learning software frameworks have been developed and are being updated frequently to adapt to new hardware features and software libraries, which bring a big ...
Chu, Xiaowen, Shi, Shaohuai, Xu, Pengfei
core +1 more source
BiomimeticsIn recent years, unmanned aerial vehicle (UAV) technology has advanced significantly, enabling its widespread use in critical applications such as surveillance, search and rescue, and environmental monitoring.
Mingen Wang +6 more
doaj +1 more source
Quantum Neural Networks: Concepts, Applications, and Challenges [PDF]
arXiv, 2021 Quantum deep learning is a research field for the use of quantum computing techniques for training deep neural networks. The research topics and directions of deep learning and quantum computing have been separated for long time, however by discovering that quantum circuits can act like artificial neural networks, quantum deep learning research is ...
arxiv
The power of microRNA regulation—insights into immunity and metabolism
FEBS Letters, EarlyView.MicroRNAs are emerging as crucial regulators at the intersection of metabolism and immunity. This review examines how miRNAs coordinate glucose and lipid metabolism while simultaneously modulating T‐cell development and immune responses. Moreover, it highlights how cutting‐edge artificial intelligence applications can identify miRNA biomarkers ...
Stefania Oliveto +2 more
wiley +1 more source