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Found 6 papers, 2 papers with code
Human-Machine Cooperative Multimodal Learning Method for Cross-subject Olfactory Preference Recognition
Secondly, a complementary multimodal data mining strategy is proposed to effectively mine the common features of multimodal data representing odor information and the individual features in olfactory EEG representing individual emotional information.
Decoding Taste Information in Human Brain: A Temporal and Spatial Reconstruction Data Augmentation Method Coupled with Taste EEG
Secondly, to avoid insufficient training of the model due to the small number of taste EEG samples, a Temporal and Spatial Reconstruction Data Augmentation (TSRDA) method was proposed, which effectively augmented the taste EEG by reconstructing the taste EEG's important features in temporal and spatial dimensions.
SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images
With the increasing demand for search and rescue, it is highly demanded to detect objects of interest in large-scale images captured by Unmanned Aerial Vehicles (UAVs), which is quite challenging due to extremely small scales of objects.
Coherent Integration for Targets with Constant Cartesian Velocities Based on Accurate Range Model
Long-time coherent integration (LTCI) is one of the most important techniques to improve radar detection performance of weak targets.
S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation
Real-time understanding in video is crucial in various AI applications such as autonomous driving.
The 1st Tiny Object Detection Challenge:Methods and Results
The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.
