From the 1 of 13 linked papers with an AI index.
13 papers
MobileSAM2: Lightweight Segment Anything for Spatial Intelligence
Kai Jiang, Jiaxing Huang, Jingyi Zhang +5
The paper introduces MobileSAM2, a lightweight version of the SAM2 segmentation model designed for mobile devices, using hypergraph-based knowledge distillation to transfer tempora…
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection
Jiaqing Zhang, Mingxiang Cao, Weiying Xie +5
Multimodal image fusion and object detection are crucial for autonomous driving. While current methods have advanced the fusion of texture details and semantic information, their c…
DiffCLIP: Few-shot Language-driven Multimodal Classifier
Jiaqing Zhang, Mingxiang Cao, Xue Yang +2
Visual language models like Contrastive Language-Image Pretraining (CLIP) have shown impressive performance in analyzing natural images with language information. However, these mo…
Towards Accurate and Efficient Sub-8-Bit Integer Training
Wenjin Guo, Donglai Liu, Weiying Xie +7
Neural network training is a memory- and compute-intensive task. Quantization, which enables low-bitwidth formats in training, can significantly mitigate the workload. To reduce qu…
Multi-scale direction-aware SAR object detection network via global information fusion
Mingxiang Cao, Weiying Xie, Jie Lei +3
Deep learning has driven significant progress in object detection using Synthetic Aperture Radar (SAR) imagery. Existing methods, while achieving promising results, often struggle…
FedFQ: Federated Learning with Fine-Grained Quantization
Haowei Li, Weiying Xie, Hangyu Ye +3
Federated learning (FL) is a decentralized approach, enabling multiple participants to collaboratively train a model while ensuring the protection of data privacy. The transmission…