This article proposes a through-wall, multi-person action recognition framework based on the improved YOLOv5 network. First, we collected the through-wall multi-person motion echoes using the IR ...

This approach significantly enhances the diversity of object sizes, backgrounds, and perspectives within the dataset. By leveraging Mosaic Data Augmentation, YOLOv5 ... missing detection of small ...

RetinaNet is a one-stage object detection model that addresses the class imbalance problem using a focal loss function, improving detection accuracy for hard-to-detect objects. Faster R-CNN is a ...

OncoSeek is a multi-cancer early detection (MCED) test using seven protein ... cell-free DNA by shallow whole-genome sequencing. In a two-step approach, the initial screening is conducted using ...

Therefore, the detection of dense small objects is challenging. A DI-YOLOv5 object detection algorithm is proposed. Specifically, a dual-wavelet convolution module (DWCM), which contains DWT_Conv and ...

Our approach allows near-sensor models to dynamically fine-tune their parameters post-deployment using online ... for the detection of FoIs. The authors utilized the YOLOv5 model family as their ...

Addressing the issues of low accuracy and slow detection speed in recognizing pointer meter readings ... Experiments were conducted using a self-made dataset of pointer-style instruments from nuclear ...

Our approach integrates lane and object detection algorithms to automate the aircraft taxiing process, ensuring collision avoidance and precise stopping. The navigation algorithm controls steering and ...

Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box ...

His object recognition software runs on a Raspberry Pi equipped with a webcam, and also makes use of Open CV. [Evan] notes that this opens up a lot of creative low-cost detection applications for ...