名称 大小
+D:\ 65个即插即用缝合模块\ 1.0 GB
+mamba 37.6 MB
+Convolutional State Space Models for Long-Range Spatiotemporal Modeling 6.4 MB
Convolutional State Space Models for Long-Range Spatiotemporal Modeling.pdf 6.0 MB
ConvSSM-main.zip 355.0 KB
+MambaIR 13.5 MB
MambaIR.pdf 3.8 MB
MambaIR-main.zip 9.8 MB
+MambaTab 641.0 KB
MambaTab.pdf 641.0 KB
+nnMamba 2.1 MB
nnMamba.pdf 1.8 MB
nnMamba-main.zip 249.0 KB
+ZigMa 14.9 MB
ZigMa.pdf 13.5 MB
zigma-main.zip 1.4 MB
+卷积 337.0 MB
+AKConv 920.0 KB
+AsymmetricConv 109.0 MB
+Chasing Higher FLOPS for Faster Neural Networks 1.3 MB
+CondConv 42.5 MB
+CoordGate 1.9 MB
+DO-Conv 4.8 MB
+DynamicConv 4.2 MB
+Efficient Deformable ConvNets Rethinking Dynamic and Sparse Operator for Vision Applications 2.7 MB
+GhostNet 4.3 MB
+HetConv 623.0 KB
+Improving Convolutional Networks with Self-Calibrated Convolutions 18.3 MB
+Involution 113.0 MB
+KernelWarehouseTowards Parameter-EffcientDynamic Convolution 12.6 MB
+OctaveConv 3.0 MB
+Omni-Dimensional Dynamic Convolution 2.2 MB
+REFCONV RE-PARAMETERIZED REFOCUSING CONVOLUTION FOR POWERFUL CONVNETS 5.7 MB
+ResNeStBlock 3.7 MB
+SCCony Spatial and Channel Reconstruction Convolution for Feature Redundancy 1.7 MB
+UniRepLKNet 5.4 MB
+十二个深度学习缝合模块Plug-and-Play-main 63.5 MB
+即插即用模块 63.5 MB
.gitigonre 5 Byte
+特征融合 275.0 MB
+Adaptive Fusion Techniques for Multimodal Data 631.0 KB
+CentralNeta Multilayer Approach forMultimodal Fusion 911.0 KB
+COMPOUND MULTI-BRANCH FEATURE FUSION FORREAL IMAGE RESTORATION 83.2 MB
+Domain Generalization for Activity Recognition viaAdaptive Feature Fusion 3.9 MB
+DSSDDeconvolutional Single Shot Detector 5.6 MB
+Effcient Low-rank Multimodal Fusion with Modality-Specifc Factors 508.0 KB
+Feature Pyramid Networks for Object Detection 109.0 MB
+FSSD Feature Fusion Single Shot Multibox Detector 13.7 MB
+LARGE-SCALE CONTRASTIVE LANGUAGE.AUDIO PRETRAINING WITFEATURE FUSION AND KEYWORD.TO-CAPTION AUGMENTATION 2.6 MB
+Learning Spatial Fusion for Single-Shot Object Detection 3.0 MB
+Multimodal Topic Learning for Video Recommendation 2.3 MB
+Rethinking Atrous Convolution for Semantic Image Segmentation 49.2 MB
+Tensor Fusion Network for Multimodal Sentiment Analysis 612.0 KB
+注意力 264.0 MB
+A2-Nets Double Attention Networks 1.0 MB
+Activating More Pixels in Image Super-Resolution Transformer 32.4 MB
+Agent Attention On the Integration of Softmax and Linear Attention 15.3 MB
+An Empirical Evaluation of Generic Convolutional and Recurrent Networks 17.2 MB
+BiFormer Vision Transformer with Bi-Level Routing Attention 11.0 MB
+CBAM Convolutional Block Attention Module 5.4 MB
+CenterMaskReal-Time Anchor-Free Instance Segmentation 11.9 MB
+CityCAN 3.7 MB
+ECA-Net Efficient Channel Attention for Deep Convolutional Neural Networks 2.5 MB
+Efficient Multi-Scale Attention Module with Cross-Spatial Learning 657.0 KB
+FECAM 8.7 MB
+Gather-Excite Exploiting Feature Context inConvolutional Neural Networks 2.3 MB
+Global Attention Mechanism Retain Information toEnhance Channel-Spatial Interactions 57.1 MB
+Global Context Networks 5.5 MB
+Large Selective Kernel Network for Remote Sensing Object Detection 16.6 MB
+Learning Dynamics and Heterogeneity ofSpatial-Temporal Graph Data for TrafficForecasting 3.6 MB
+Non-local Neural Networks 9.7 MB
+Non-stationary Transformers 6.7 MB
+On the Integration of Self-Attention and Convolution 2.0 MB
+Polarized Self-Attention Towards High-quality Pixel-wise Regression 9.3 MB
+PYRAFORMER LOW-COMPLEXITY PYRAMIDAL 12.2 MB
+REVERSIBLE COLUMN NETWORKS 2.5 MB
+SEAFORMER 5.3 MB
+Selective Kernel Networks 5.9 MB
+Self-supervised Equivariant Attention Mechanismfor Weakly Supervised Semantic Segmentation 3.4 MB
+Squeeze-and-Excitation Networks 2.9 MB
+Triformer 9.0 MB
+UnetTSF A Better Performance Linear Complexity Time Series Prediction Model 720.0 KB