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A Single-Stage 3D Object Detection Method Based on Sparse Attention Mechanism
The Bird’s Eye View (BEV) feature extraction module is an important part of 3D object detection based on point cloud data. However, the existing...
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SSA: A Content-Based Sparse Attention Mechanism
Recently, many scholars have used attention mechanisms to achieve excellent performance results on various neural network applications. However, the...
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TST: Time-Sparse Transducer for Automatic Speech Recognition
End-to-end model, especially Recurrent Neural Network Transducer (RNN-T), has achieved great success in speech recognition. However, transducer...
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A Hybrid Synchronization Mechanism for Parallel Sparse Triangular Solve
Sparse triangular solve, SpTS, is an important and recurring component of many sparse linear solvers that are extensively used in many big-data...
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Hierarchical reinforcement learning for handling sparse rewards in multi-goal navigation
Reinforcement learning (RL) has achieved remarkable advancements in navigation tasks in recent years. However, tackling multi-goal navigation tasks...
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SG-NeRF: Sparse-Input Generalized Neural Radiance Fields for Novel View Synthesis
Traditional neural radiance fields for rendering novel views require intensive input images and pre-scene optimization, which limits their practical...
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Spatial Gene Expression Prediction Using Hierarchical Sparse Attention
Spatial Transcriptomics (ST) quantitatively interprets human diseases by providing the gene expression of each fine-grained spot (i.e., window) in a...
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SWG: an architecture for sparse weight gradient computation
On-device training for deep neural networks (DNN) has become a trend due to various user preferences and scenarios. The DNN training process consists...
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Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms
Private selection algorithms, such as the exponential mechanism, noisy max and sparse vector, are used to select items (such as queries with large...
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Cancellable biometrics based on the index-of-maximum hashing with random sparse binary encoding
The wide deployment of biometrics has prompted enormous security and privacy concerns regarding biometric template protection. Cancellable biometrics...
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Sparse spatial transformers for few-shot learning
Learning from limited data is challenging because data scarcity leads to a poor generalization of the trained model. A classical global pooled...
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Non-linear Feature Selection Based on Convolution Neural Networks with Sparse Regularization
The efficacy of feature selection methods in dimensionality reduction and enhancing the performance of learning algorithms has been well documented....
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Stereo-RSSF: stereo robust sparse scene-flow estimation
Scene-flow (SF) estimation is considered to be one of the most fundamental problems in scene understanding and autonomous control. The majority of...
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A weighted multi-view clustering via sparse graph learning
Multi-view clustering considers the diversity of different views and fuses these views to produce a more accurate and robust partition than...
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Clustering by sparse orthogonal NMF and interpretable neural network
Employing differentiable reconstruction to interpret the clustering layers of neural networks presents a potent solution to the interpretability...
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A Time-Series-Based Sample Amplification Model for Data Stream with Sparse Samples
The data stream is a dynamic collection of data that changes over time, and predicting the data class can be challenging due to sparse samples,...
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Intensifying graph diffusion-based salient object detection with sparse graph weighting
Salient object detection based on the diffusion process on the graph has achieved considerable performance. It mainly depends on the affinity matrix...
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Sparse Graph Hashing with Spectral Regression
Learning-based hashing has received increasing research attention due to its promising efficiency for large-scale similarity search. However, most...
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Facial micro-expression recognition using three-stream vision transformer network with sparse sampling and relabeling
Most existing micro-expression recognition (MER) methods are based on convolutional neural networks (CNN) and could obtain better representations...
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A Sparse Self-Attention Enhanced Model for Aspect-Level Sentiment Classification
Aspect based sentiment analysis (ABSA) manifests the well refined work as Aspect-level sentiment classification (ASC) due to recent high attention...
