Description
A capsule is an activation vector that basically executes on its inputs some complex internal computations. Length of these activation vectors signifies the probability of availability of a feature. Furthermore, the condition of the recognized element is encoded as the direction in which the vector is pointing. In traditional, CNN uses Max pooling for invariance activities of neurons, which is nothing except a minor change in input and the neurons of output signal will remains same.
Papers Using This Method
Attonsecond Streaking Phase Retrieval Via Deep Learning Methods2025-05-06Self-Supervised Learning for Pre-training Capsule Networks: Overcoming Medical Imaging Dataset Challenges2025-02-07Graph-Driven Models for Gas Mixture Identification and Concentration Estimation on Heterogeneous Sensor Array Signals2024-12-18ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis2024-11-03Mitigating Vanishing Activations in Deep CapsNets Using Channel Pruning2024-10-22Deep Hybrid Architecture for Very Low-Resolution Image Classification Using Capsule Attention2024-09-27MIMNet: Multi-Interest Meta Network with Multi-Granularity Target-Guided Attention for Cross-domain Recommendation2024-07-31Deep multi-prototype capsule networks2024-04-23OrthCaps: An Orthogonal CapsNet with Sparse Attention Routing and Pruning2024-03-20Leveraging Spatial and Semantic Feature Extraction for Skin Cancer Diagnosis with Capsule Networks and Graph Neural Networks2024-03-18Masked Capsule Autoencoders2024-03-07DTCM: Deep Transformer Capsule Mutual Distillation for Multivariate Time Series Classification2024-02-26InceptionCapsule: Inception-Resnet and CapsuleNet with self-attention for medical image Classification2024-02-03Improved efficient capsule network for Kuzushiji-MNIST benchmark dataset classification2023-12-15Predicting Transcription Factor Binding Sites using Transformer based Capsule Network2023-10-23Lie Group Decompositions for Equivariant Neural Networks2023-10-171D-CapsNet-LSTM: A Deep Learning-Based Model for Multi-Step Stock Index Forecasting2023-10-03A Model-Agnostic Framework for Recommendation via Interest-aware Item Embeddings2023-08-17Novel Nonlinear Neural-Network Layers for High Performance and Generalization in Modulation-Recognition Applications2023-08-14ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method2023-07-19