Fully Connected Layer
الطبقة كاملة الاتصال
طبقة تتشابك فيها كافة العصبونات مع مخرجات المستوى السابق بالكامل لدمج ميزات التصنيف النهائي.
Fully Connected Layer
Also translated asالمستوى الشامل لتشابك العصبونات، الطبقة الكثيفة الروابط
First appears in this corpus in: Gradient-Based Learning Applied to Document Recognition (1998)
Appears in these papers
- ImageNet Classification with Deep Convolutional Neural Networks2012in the sky ✦
- Mastering the Game of Go Without Human Knowledge2017in the sky ✦
- A General Reinforcement Learning Algorithm That Masters Chess, Shogi, and Go Through Self-Play2018in the sky ✦
- BLIP-2: Bootstrapping Language-Image Pre-Training with Frozen Image Encoders and Large Language Models2023in the sky ✦
- Dynamic Routing Between Capsules2017in the sky ✦
- Unsupervised Visual Representation Learning by Context Prediction2015in the sky ✦
- Gradient-Based Learning Applied to Document Recognition1998in the sky ✦
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks2015in the sky ✦
- Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding2016in the sky ✦
- Deep Speech 2: End-to-End Speech Recognition in English and Mandarin2015in the sky ✦
- Deformable Convolutional Networks2017in the sky ✦
- Deep Interest Network for Click-Through Rate Prediction2018in the sky ✦
- Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World2017in the sky ✦
- Human-Level Control Through Deep Reinforcement Learning2015in the sky ✦
- Dueling Network Architectures for Deep Reinforcement Learning2016in the sky ✦
- Fast R-CNN2015in the sky ✦
- Fast R-CNN2015in the sky ✦
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks2015in the sky ✦
- Fully Convolutional Networks for Semantic Segmentation2015in the sky ✦
- Going Deeper with Convolutions2014in the sky ✦
- Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization2017in the sky ✦
- Inductive Representation Learning on Large Graphs2017in the sky ✦
- IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures2018in the sky ✦
- Mask R-CNN2017in the sky ✦
- MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications2017in the sky ✦
- N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting2019in the sky ✦
- N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting2019in the sky ✦
- NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis2020in the sky ✦
- PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation2017in the sky ✦
- Deep Residual Learning for Image Recognition2015in the sky ✦
- Shampoo: Preconditioned Stochastic Tensor Optimization2018in the sky ✦
- Spatial Transformer Networks2015in the sky ✦
- Very Deep Convolutional Networks for Large-Scale Image Recognition2014in the sky ✦
- Very Deep Convolutional Networks for Large-Scale Image Recognition2014in the sky ✦
- End-to-End Training of Deep Visuomotor Policies2016in the sky ✦
- VQA: Visual Question Answering2015in the sky ✦
- You Only Look Once: Unified, Real-Time Object Detection2015in the sky ✦
- YOLOv3: An Incremental Improvement2018in the sky ✦