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FormerReckoning: Physics Inspired Transformer for Accurate Inertial Navigation
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RREH: Reconstruction Relations Embedded Hashing for Semi-Paired Cross-Modal Retrieval
Known for efficient computation and easy storage, hashing has been extensively explored in cross-modal retrieval. The majority of …
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RREH: Reconstruction Relations Embedded Hashing for Semi-Paired Cross-Modal Retrieval
Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning
Single-model systems often suffer from deficiencies in tasks such as speaker verification (SV) and image classification, relying …
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Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning
Enhancing Anomalous Sound Detection with Multi-Level Memory Bank
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Enhancing Anomalous Sound Detection with Multi-Level Memory Bank
PRENet: A Plane-Fit Redundancy Encoding Point Cloud Sequence Network for Real-Time 3D Action Recognition
Recognizing human actions from point cloud sequence has attracted tremendous attention from both academia and industry due to its wide …
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PRENet: A Plane-Fit Redundancy Encoding Point Cloud Sequence Network for Real-Time 3D Action Recognition
Gecko: Resource-Efficient and Accurate Queries in Real-Time Video Streams at the Edge
Surveillance cameras are ubiquitous nowadays and users’ increasing needs for accessing real-world information (e.g., finding abandoned …
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Gecko: Resource-Efficient and Accurate Queries in Real-Time Video Streams at the Edge
Value-Driven Mixed-Precision Quantization for Patch-Based Inference on Microcontrollers
Deploying neural networks on microcontroller units (MCUs) presents substantial challenges due to their constrained computation and …
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Value-Driven Mixed-Precision Quantization for Patch-Based Inference on Microcontrollers
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection
Detecting out-of-distribution (OOD) examples is crucial to guarantee the reliability and safety of deep neural networks in real-world …
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GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection
Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning
This paper proposes Shoggoth, an efficient edge-cloud collaborative architecture, for boosting inference performance on real-time video …
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Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning
AOSR-Net: All-in-One Sandstorm Removal Network
Most existing sandstorm image enhancement methods are based on traditional theory and prior knowledge, which often limit their …
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AOSR-Net: All-in-One Sandstorm Removal Network