Fall detectionDeep Convolution Neural Network-DCNNSpatial-Temporal Graph Convolution Network-ST-GCNDaily Living Activities-ADLMost recently, Human fall detection systems using deep learning models find major applications in all fields, especially in the held of healthcare. Even without doctor analysis, ...
MiM-ISTD (Chen et al., 2024h) Apr 2024, arXiv Infrared Small Target Detection Nested structure with Outer and Inner Mamba blocks for efficient feature capture NUAA-SIRST, IRSTD-1K Datasets SOAR (Verma et al., 2024) May 2024, arXiv Aerial Small Object Detection Vision Mamba-based YOLO ...
On top of that, we also introduce a Swin-Transformer-based UNet architecture, called Swinv2-Unet, which can address the problems stemming from the CNN convolution operations. Extensive experiments are conducted to evaluate the performance of the proposed model by using three real-world datasets, i...
As shown in Figure 3, feature extraction methods fall into two main categories: DL-based and handcrafted. DL-based methods automatically extract features from raw gait data (e.g., images, video frames, or silhouettes) using DL models, such as CNNs, recurrent neural networks (RNNs), or ...
AI-based systems can also automate processes such as repair planning, optimizing operational workflows, and minimizing resource waste [22]. The existing studies have been summarized in Table 1. However, existing studies have focused only on the detection accuracy without ad- dressing operational ...