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Longer titles found: Deep learning in photoacoustic imaging (view), Deep learning speech synthesis (view), Transformer (deep learning architecture) (view), Comparison of deep learning software (view), Deep Learning Super Sampling (view), Deep Learning Anti-Aliasing (view), Layer (deep learning) (view), Inception (deep learning architecture) (view), Deep Learning Studio (view), Fine-tuning (deep learning) (view), Mamba (deep learning architecture) (view)

searching for Deep learning 127 found (1997 total)

alternate case: deep learning

Anti-aliasing (653 words) [view diff] exact match in snippet view article find links to article

anti-aliasing Deep learning anti-aliasing (DLAA), a type of spatial and temporal anti-aliasing method relying on dedicated tensor core processors Deep learning super

Super-resolution imaging (SR) is a class of techniques that improve the resolution of an imaging system. In optical SR the diffraction limit of systems

consumer/gamer products, the Instinct product line is intended to accelerate deep learning, artificial neural network, and high-performance computing/GPGPU applications

Closes $9 Million in Series A Financing to Further Achievements in Deep Learning" (Press release). Maluuba Inc. 20 January 2016. Retrieved 2 April 2016

poet Giosuè Carducci (1835–1907) "not only in consideration of his deep learning and critical research, but above all as a tribute to the creative energy

reconstruction methods with deep learning reconstruction prior is also an alternative approach to improve the image quality of deep learning reconstruction. Tomographic

Provencher, Benjamin; McKee, Marc D.; Piché, Nicolas (October 2020). "Deep learning for 3D imaging and image analysis in biomineralization research". Journal

companies, such as Chemical.AI, Reaxys, etc., have started to integrate deep learning into the conventional rule-based approaches. Disconnection A retrosynthetic

Autoencoders. Deep learning has been applied to many scenarios (context-aware, sequence-aware, social tagging etc.). However, deep learning effectiveness

generalized information criterion (GIC), the model-X knockoffs (MXK), the deep learning inference using knockoffs (DeepLINK), and the statistical inference

Skansi, Sandro (ed.), "AI-Completeness: Using Deep Learning to Eliminate the Human Factor", Guide to Deep Learning Basics: Logical, Historical and Philosophical

computer vision. By developing smaller DNNs, the firm has been able to run deep learning on scaled-down processing hardware such as smartphones and automotive-grade

multiple tasks and domains. MS MARCO has also been adopted in the TREC Deep Learning Tracks, where it serves as a core dataset for evaluating advances in

is Ceva's family of low-power artificial intelligence processors for deep learning. NeuPro processors are self-contained, specialized AI processors, scaling

Swedish Academy awarded him the prize "not only in consideration of his deep learning and critical research, but above all as a tribute to the creative energy

An end-to-end deep learning framework for protein structure prediction Webserver and downloadable program D-I-TASSER The deep learning-based I-TASSER

line competed with AMD's Radeon Instinct and Intel Xeon Phi lines of deep learning and GPU cards. Nvidia retired the Tesla brand in May 2020, reportedly

synthesis are often facilitated through the use of spectrograms. In deep learning-keyed speech synthesis, spectrogram (or spectrogram in mel scale) is

comma.ai. Since November 2022, Hotz has been working on tinygrad, a deep learning framework. Hotz attended the Academy for Engineering and Design Technology

content and collaborative data In recent years a number of neural and deep-learning techniques have been proposed, some of which generalize traditional

data-intensive machine learning methods to biological data, such as deep learning (DL), reinforcement learning (RL), and their combination (deep RL).

Growth. In: Hong, TP., Serrano-Estrada, L., Saxena, A., Biswas, A. (eds) Deep Learning for Social Media Data Analytics. Studies in Big Data, vol 113. Springer

teams, we see that people are changed, often profoundly. There is a deep learning cycle. Team members develop new skills, and capabilities which alter

to feature Tensor Cores, specially designed cores that have superior deep learning performance over regular CUDA cores. The architecture is produced with

processing images in particular. Deep learning processors, such as neural processing units are designed for efficient deep learning computation. Physics processing

challenges in data interpretation and storage. However, with the advent of deep learning, a branch of machine learning and artificial intelligence, and it has

SimpleElastix medical image registration library, and the NiftyNet deep learning library for medical imaging. The initial development of SimpleITK was

products. In the check-out phase, stores utilize sensor fusion and deep learning for computer vision to allow customers to walk out with their products

significant result compared to the background. Triplexfpp is based on deep learning methods. This Python-based pipeline can help predict the most likely

Buytaert Drupal Content management framework François Chollet Keras Deep learning framework Evan Czaplicki Elm Front-end web programming language Laurent

Gradient Symbolic Computation has been embedded in neural networks using deep learning to address a range of problems in reasoning and natural language processing

interests of applying deep learning techniques to de novo peptide sequencing. In 2017 Tran et al. proposed DeepNovo, the first deep learning based de novo sequencing

distributions while jointly learning representations of the input covariates. Deep learning approaches have shown superior performance especially on complex input

Distributed scheduling queues (4 scheduling queues, up from 2) Intel Deep Learning Boost, used for machine learning/artificial intelligence inference acceleration

Senior Staff Engineer at Google. Chollet is the creator of the Keras deep-learning library, released in 2015. His research focuses on computer vision,

involve similar statistical techniques as power-analysis attacks. A deep-learning-based side-channel attack, using the power and EM information across

needed] It is still commonly used, however, for variational methods in Deep Learning, such as variational autoencoders, where latent variable spaces are

Deep Learning From Basics to Practice. In July 2019, he took up a position as senior research scientist at visual effects company Weta Digital. Deep Learning

technology, using deep learning-based artificial intelligence (AI) which were developed by NTT Communication. According to the article "Deep-learning-based", "The

In 2015 Nielsen published the online textbook Neural Networks and Deep Learning, and joined the Recurse Center as a Research Fellow for a year. He then

more accurately by an artificial intelligence system (which used a deep learning convolutional neural network) than by dermatologists. On average, the

"microsoft/nni". August 11, 2020 – via GitHub. Gridin, Ivan (2022). Automated Deep Learning Using Neural Network Intelligence: Develop and Design PyTorch and TensorFlow

Robust Principal Component Analysis (RPCA) is a modification of the widely used statistical procedure of principal component analysis (PCA) which works

job of synthesis and interpretation that reflects Eugen's wide and deep learning," by his UCLA history colleague Hans Rogger. In addition to his distinguished

Unit (VPU) built-in for accelerating inference for computer vision and deep learning. Adapteva Epiphany, a manycore processor with similar emphasis on on-chip

Craftsman Capital Partners later in 2017. Cirrascale Cloud Services offers deep learning infrastructure solutions[buzzword] for self-driving vehicles, medical

learning platform that are powered by a combination of machine learning, deep learning and natural language processing to produce an automated and holistic

regression and naive Bayes with the highest accuracy obtained with deep learning. This was later extended "Deep Cytometry" in which the computationally

research involves developing and applying statistical methods and machine/deep learning in nanoscience and nanotechnology, and materials and molecular informatics

Sejnowski in Artificial Intelligence: The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence". Mathematician and Turing Award laureate

taken. As expected, the combination of both uncertainty estimation and deep learning for imputation is among the best strategies and has been used to model

Network's mission is to promote trust in social media by utilizing Deep Learning and AI. The platform leverages world's first and only tokenized Social

Mucilage Extraction Index (AMEI). By employing spectral indices and deep learning methods like Convolutional Neural Networks (CNNs), researchers can improve

Khalid (ed.), "Chapter 18 - Deep learning in predicting genetic disorders: A case study of diabetic kidney disease", Deep Learning in Genetics and Genomics

APIs spans several domains, including libraries for linear algebra, deep learning, machine learning, video processing, and others. The source code of

Prentice-Hall. ISBN 978-0-13-221581-7. Wang, Yinpeng; Ren, Qiang (2024). Deep learning-based forward modeling and inversion techniques for computational physics

outcomes. Additionally, deep learning models have allowed NPCs to become more capable of predicting players behaviors. Deep learning allows NPCs to process

of deep learning include using large time steps and improving the accuracy of finite differences for high frequencies on coarse grids. Other deep learning

deep learning, enhanced word, variable precision. AVX-512 Fused Multiply Accumulation Packed Single precision (4FMAPS) – vector instructions for deep

Multisample anti-aliasing Fast approximate anti-aliasing Deep learning super sampling Deep learning anti-aliasing Supersampling Deinterlacing Spatial anti-aliasing

Recognition and Pattern Recognition and Machine Learning. His latest book, Deep Learning, Foundations and Concepts, was published in 2023 by Springer. Bishop

Chai, Wei (2016-06-24). "Wide & Deep Learning for Recommender Systems". arXiv:1606.07792 [cs.LG]. "Wide & Deep Learning: Better Together with TensorFlow"

in v9.0. CuPy has been initially developed as a backend of Chainer deep learning framework, and later established as an independent project in 2017.

as an alternative spelling of café Caffe (software), a library for deep learning Caffa (disambiguation) This disambiguation page lists articles associated

Boca Raton, FL: CRC Press. ISBN 978-1-4822-1118-4. "How to Parallelize Deep Learning on GPUs Part 2/2: Model Parallelism". Tim Dettmers. 2014-11-09. Retrieved

Hopf–Whitney theorem. Recently, homotopy theory is used to develop deep learning based generative models like diffusion models and flow-based generative

intelligence and deep learning, including: self-driving cars, healthcare, high performance computing, professional visualization, and Nvidia Deep Learning Institute

.400D. doi:10.1137/0719025. JSTOR 2156954.. Martens, James (2010). Deep learning via Hessian-free optimization (PDF). Proc. International Conference

her first major solo museum exhibition, Deep Learning at The Aldrich Contemporary Art Museum. Deep Learning debuted a series of paintings and digital

Mateev. The company claims to use highly sparse neural networks to make deep learning computationally so efficient that GPUs won't be needed. For certain

generation to support 3D XPoint-based memory modules. It also features Deep Learning Boost (DPL) instructions and mitigations for Meltdown and Spectre. Intel

induprotx.com/.] Hannigan, Geoffrey; Prihoda, David; et al. 2019. "A deep learning genome-mining strategy for biosynthetic gene cluster prediction". Nucleic

Learning with Spark – Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More. Apress. ISBN 978-1-4842-5668-8. van Wyk, Andrich

intrusion detection system: A systematic study of machine learning and deep learning approaches". Transactions on Emerging Telecommunications Technologies

cosmology, deep learning and its applications in astrophysics and data science. In particular, she is interested in developing and deploying deep learning to

4.541. LeCun, Yann (2016). "Slides on Deep Learning Online". "Unsupervised Feature Learning and Deep Learning Tutorial". ufldl.stanford.edu. Hinton,

Corporation, Princeton University, and other institutions are leveraging deep learning to teach computers to anticipate subsequent road scenarios based on

Retrieved 2015-07-22. Ramsundar, Bharath (2019). Deep Learning for the Life Sciences : Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and

unexpected and cross-domain recommendations based on the principles of deep-learning, developing novel approaches to customer segmentation, and discovery

instructions for deep learning. AVX-512 Fused Multiply Accumulation Packed Single precision (4FMAPS) – vector instructions for deep learning. VPOPCNTDQ –

structure in computer science 0th law of Thermodynamics Zeroth (software), deep learning software for mobile devices 0th grade, another name for kindergarten

Nobel Prize in Literature in 1906 "not only in consideration of his deep learning and critical research, but above all as a tribute to the creative energy

Secondary School or officially Comprehensive Secondary School No.189 with deep learning of English and German from the first grade of Desna raion of Kyiv municipality

The review extends into considerations of video color transfer and deep learning methods including Neural style transfer. Color transfer processing can

Intelligence Service. MI-6 or MI6 may also refer to: AMD's MI6, a brand of deep learning oriented Graphics Processing Units, see Radeon Instinct Mil Mi-6, a

In computational physics, variational Monte Carlo (VMC) is a quantum Monte Carlo method that applies the variational method to approximate the ground state

Arpit (ed.). "Analysis of Traditional Cultural Acceptance Based on Deep Learning". Computational Intelligence and Neuroscience. 2022: 1–8. doi:10.1155/2022/2373842

structure-based prediction of binding specificity across protein families using deep learning. Protein–DNA interactions occur when a protein binds a molecule of DNA

opposite directions to the same output. With this form of generative deep learning, the output layer can get information from past (backwards) and future

S; Acharya, UR (27 May 2021). "Epileptic Seizures Detection Using Deep Learning Techniques: A Review". International Journal of Environmental Research

hierarchical memory network. Most of the contemporary methods for ERC are deep learning based and rely on the idea of latent speaker-state modeling. Recently

coverage regarding investigations into the theoretical foundations of deep learning, and work forecasting COVID-19 severity in the US. Other research topics

has also been performed to test the diagnostic performance of Aidoc's deep learning-based triage system for the flagging of acute findings in abdominal

MathWorks For logical FPGA and ASIC designs Deep Learning HDL Toolbox - Prototype and deploy deep learning networks on FPGAs and SoCs DSP HDL Toolbox -

The NVIDIA Deep Learning Accelerator (NVDLA) is an open-source hardware neural network AI accelerator created by Nvidia. The accelerator is written in

basis of a new approach to deep learning that was until now considered as a form of multi-layered neural networks. Deep Learning offers high precision levels

human emotional states. OpenAI's CLIP model exemplifies the use of deep learning to associate images and text, facilitating nuanced understanding of

aid of artificial intelligence, investors are increasingly turning to deep learning techniques to forecast and analyze trends in stock and foreign exchange

Chips&Media Specializes in video codecs, image signal processing, and deep learning-based computer vision system (super-resolution). Google (through acquisition

Rodriguez-Prieto; Alejandro Pato; Francisco Ortin (2025). "PLangRec: Deep-learning model to predict the programming language from a single line of code"

Alcock was one of the leading pre-Reformation divines; he was a man of deep learning and also of great proficiency as an architect. Besides founding a charity

Embryo Ranking Intelligent Classification Algorithm (ERICA) is a deep learning AI software designed to assist embryologists and clinicians during the

(October 26, 2016). "AI Pioneer Yoshua Bengio Is Launching Element.AI, a Deep-Learning Incubator". Wired. Retrieved February 1, 2019. "Element AI receives

Daniel Tamayo, Kristen Menou) (2019). "Lunar Crater Identification via Deep Learning". Icarus. 317: 27–38. arXiv:1803.02192. Bibcode:2019Icar..317...27S

online courses in a range of subjects that include Neural Networks and Deep Learning, Probabilistic Graphical Models, Machine Learning, Big Data, Hadoop

reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent". Sci Rep. 7: 46450. doi:10.1038/srep46450

families of models: tensor decomposition models, geometric models, and deep learning models. The tensor decomposition is a family of knowledge graph embedding

face, vocal intonations and body posture. Affectiva's AI is built with deep learning, computer vision, and large amounts of data that has been collected

Specialized School or officially the Kyiv Specialized School No.98 with deep learning of English (Ukrainian: Київська спеціалізована школа № 98 з поглибленим

Massachusetts. The company is known for the development of a series of deep learning algorithms that are used to analyze and recommend books. Since its founding

Jawarneh, Ibrahim & Alsharman, Nesreen (2021). "The Mathematical Model and Deep Learning Features Selection for Whorl Fingerprint Classifications". International

Growth. In: Hong, TP., Serrano-Estrada, L., Saxena, A., Biswas, A. (eds) Deep Learning for Social Media Data Analytics. Studies in Big Data, vol 113. Springer

your own "Watson Jr." in your basement, Inside System Storage "DGX-1 deep learning system" (PDF). NVIDIA DGX-1 Delivers 75X Faster Training...Note: Caffe

called the connecting link between Origen and the Coptic monks. A man of deep learning and prodigious memory, he seems to have developed Origen's Christology

including Microsoft, Google, Amazon and IBM. Birrell is researching deep learning and robotics at Cambridge University. He is the author of the blog Artificial

BEng’86, MSc’88, PhD’91, has well-recognized work in the field of deep learning and artificial neural webworks. He was co-recipient of the A.M Turing

17, 2014. Retrieved July 17, 2014 – via Twitter. "Twitter acquires deep learning startup Madbits". Gigaom. July 29, 2014. Retrieved April 4, 2016. "Mitro

for sampling applications: A case study with possible applications in deep learning". Physical Review A. 94 (2): 022308. arXiv:1510.07611. Bibcode:2016PhRvA

(2019). "Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathematical programming". Computers &

readable images that are free from artefacts. She took part in the 2017 Deep Learning in Healthcare Summit in Boston. She was awarded a 2018 Johns Hopkins

continuous updates contributes to fragmented attention, making sustained, deep learning more difficult. Another concern is the impact of media multitasking

Letters 92, 111102, 2008. [11] C. Chen, A. Mahjoubfar, & B. Jalali, "Deep Learning in Label-free Cell Classification," Scientific Reports 6, 21471 (2016)

for any underlying point predictor (whether statistical, machine, or deep learning) only assuming exchangeability of the data. CP works by computing nonconformity

The companies focus on using inflection points in medicine, such as deep learning, next-generation sequencing, and the silicon supply chain, to address

least due to its applicability as an input layer for neurally inspired deep learning models, lexical semantics, i.e. the meaning of words, will only carry

cloud AI. OpenAI estimated the hardware compute used in the largest deep learning projects from Alex Net (2012) to Alpha Zero (2017), and found a 300

version got online. April 2018, New functions include Trend Analysis, a deep learning based Name Disambiguation AMiner published several datasets for academic