Search for "Deep learning" in article titles:

1. Deep learning: Deep Learning has revolutionised Pattern Recognition and Machine Learning. It is about credit assignment in adaptive systems with long chains of potentially causal links between actions and consequences. [100%] 2021-12-21
2. Deep learning: Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. (Branch of machine learning) [100%] 2022-07-29 [Deep learning] [Artificial neural networks]...
3. Deep learning: According to Wikipedia (Oct 27 2016), “Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in ... [100%] 2024-01-19
4. Deep learning: Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. (Branch of machine learning) [100%] 2021-12-22 [Deep learning] [Artificial neural networks]...
5. Deep learning processor: A deep learning processor (DLP), or a deep learning accelerator, is an electronic circuit designed for deep learning algorithms, usually with separate data memory and dedicated instruction set architecture. Deep learning processors range from mobile devices, such as neural processing ... (Specially designed circuitry) [81%] 2023-04-08 [Computer optimization] [Deep learning]...
6. Deep learning anti-aliasing: Deep learning anti-aliasing (DLAA) is a form of spatial anti-aliasing created by Nvidia. DLAA depends on and requires Tensor Cores available in Nvidia RTX cards. (Computer Graphics Anti-Aliasing Algorithm) [81%] 2023-12-15 [Anti-aliasing algorithms]
7. Deep learning anti-aliasing: Deep learning anti-aliasing (DLAA) is a form of spatial anti-aliasing created by Nvidia. DLAA depends on and requires Tensor Cores available in Nvidia RTX cards. (Computer Graphics Anti-Aliasing Algorithm) [81%] 2023-05-05 [Anti-aliasing algorithms]
8. Deep learning super sampling: Deep learning super sampling (DLSS) is a family of real-time deep learning image enhancement and upscaling technologies developed by Nvidia that are exclusive to its RTX line of graphics cards, and available in a number of video games. The ... (Image upscaling technology by Nvidia) [70%] 2023-10-25 [Graphics processing units] [3D computer graphics]...
9. Deep learning speech synthesis: Deep learning speech synthesis uses Deep Neural Networks (DNN) to produce artificial speech from text (text-to-speech) or spectrum (vocoder). The deep neural networks are trained using a large amount of recorded speech and, in the case of a ... (A method of speech synthesis that uses deep neural networks) [70%] 2023-02-02 [Speech synthesis] [Applications of artificial intelligence]...
10. Deep learning super sampling: Deep learning super sampling (DLSS) is a family of real-time deep learning image enhancement and upscaling technologies developed by Nvidia that are available in a number of video games. The goal of these technologies is to allow the majority ... (Image upscaling technology by Nvidia) [70%] 2025-01-08 [3D computer graphics] [Nvidia]...
11. Deep learning in photoacoustic imaging: Deep learning in photoacoustic imaging combines the hybrid imaging modality of photoacoustic imaging (PA) with the rapidly evolving field of deep learning. Photoacoustic imaging is based on the photoacoustic effect, in which optical absorption causes a rise in temperature, which ... [63%] 2024-06-13 [Deep learning] [Medical imaging]...
12. Deep Learning: Deep Learning has revolutionised Pattern Recognition and Machine Learning. It is about credit assignment in adaptive systems with long chains of potentially causal links between actions and consequences. [100%] 2021-12-21
13. Deep Learning: Deep Learning (deutsch mehrschichtiges Lernen, tiefes Lernen oder tiefgehendes Lernen) bezeichnet eine Methode des maschinellen Lernens, die künstliche neuronale Netze (KNN) mit zahlreichen Zwischenschichten (englisch hidden layers) zwischen Ein- und Ausgabeschicht einsetzt und dadurch eine umfangreiche innere Struktur herausbildet. [100%] 2025-06-20
14. Deep reinforcement learning: Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to make decisions by trial and error. (Machine learning that combines deep learning and reinforcement learning) [81%] 2023-12-10 [Machine learning algorithms] [Reinforcement learning]...
15. Layer (deep learning): A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and then passes it to the next layer. The first type of layer is the ... (Deep learning) [81%] 2024-01-21 [Artificial neural networks]
16. Layer (deep learning): A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and then passes it to the next layer. The first type of layer is the ... (Deep learning) [81%] 2024-01-04 [Artificial neural networks]
17. Deep Learning Studio: Deep Learning Studio is a software tool that aims to simplify the creation of deep learning models used in artificial intelligence. It is compatible with a number of open-source programming frameworks popularly used in artificial neural networks, including MXNet ... (Software) [81%] 2023-02-02
18. Layer (deep learning): A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and then passes it to the next layer. The first type of layer is the ... (Deep learning) [81%] 2023-10-25 [Artificial neural networks]
19. Topological Deep Learning: Topological deep learning (TDL) represents a field at the intersection of topology and deep learning, offering approaches to analyze and learn from data structured in topological spaces. By leveraging the principles of topology, TDL offers an approach to understanding and ... [81%] 2024-03-21
20. Topological deep learning: Topological deep learning (TDL) represents a field at the intersection of topology and deep learning, offering approaches to analyze and learn from data structured in topological spaces. By leveraging the principles of topology, TDL offers an approach to understanding and ... [81%] 2024-03-29 [Deep learning] [Topology]...
21. Deep Learning Studio: Deep Learning Studio is a software tool that aims to simplify the creation of deep learning models used in artificial intelligence. It is compatible with a number of open-source programming frameworks popularly used in artificial neural networks, including MXNet ... (Software tool) [81%] 2024-06-11 [Deep learning software]
22. Transformer (deep learning architecture): A transformer is a deep learning architecture developed by Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need". Text is converted to numerical representations called tokens, and each token is ... (Deep learning architecture) [70%] 2024-06-17 [Google software] [Neural network architectures]...
23. Comparison of deep-learning software: The following table compares notable software frameworks, libraries and computer programs for deep learning. (Software) [63%] 2023-10-04 [Applied machine learning] [Comparisons of mathematical software]...
24. Comparison of deep learning software: The following table compares notable software frameworks, libraries and computer programs for deep learning. (None) [63%] 2023-10-04 [Applied machine learning] [Comparisons of mathematical software]...
25. JDLA Deep Learning For GENERAL: JDLA Deep Learning for GENERAL（JDLAディープラーニングフォージェネラル）は、一般社団法人日本ディープラーニング協会（JDLA）が実施するAIに関する検定試験および民間資格である。 特にディープラーニングの基礎知識を有し、適切な活用方針を決定して事業応用する能力を持つ人材の輩出を目的として実施されている。ディープラーニングの技術が日進月歩する技術であることから検定・資格実施毎に実施年号を付与している。一般にG検定（ジーけんてい）またはG検（ジーけん）と呼ばれる。G検定のGはジェネラルの意味である。 2020年3月までの試験に関しては、オンライン受験（自宅受験）・多肢選択式・2時間で225問程度の問題が出題されており、試験中にテキストの閲覧やインターネットを通じた. [63%] 2024-10-29 [2017年設立] [機械学習]...