The output of TAO is a trained model in ONNX format that can be deployed on any platform that supports ONNX. TAO Overview Image TAO supports most of the popular CV tasks such as: Image Classification Multi-Model Sensor Fusion for computer vision Object Detection Instance Segmentation Semantic ...
Small object detection complex background feature image preprocessing machine learning We recommend PAW-YOLOv7: algorithm for detection of tiny floating objects in river channels Opto-Electronic Engineering,2024 Small object detection based on multi-scale feature fusion using remote sensing images ...
RetailObjectRecognition ResNet-101 83.66% mAP Object recognition in a retail checkout. Note The accuracy reported for BodyPoseNet is based on a model trained using the COCO dataset. To reproduce the same accuracy, use the sample notebook. Performance Metrics The performance of these pretrained ...
Figure 2. Introduction of the YOLO algorithm and its application and development trend in industry. 2. Algorithm Introduction Before the proposal of the YOLO series algorithms, the mainstream object detection algorithms based on deep learning used object classification to detect target objects. At the...
4. The k-means clustering algorithm is used to yield anchor boxes. 5. Multi-scale training. 1. Difficult in detecting small objects. 2. Complex training. YOLO v3 [33] 2018 Fixed Darknet-53 SGD Binary cross entropy 1. To boost the multi-scale detection accuracy, it makes use of multi-...
highly energy-efficient hardware engines are required to extend the existing accelerators to a broad spectrum of challenging scenarios. To address the aforementionedgrand challenges, massive innovations of computer vision systems, in terms of both algorithm developments and hardware designs, are expected ov...
In recent years, agriculture has become a major field of application and transfer for AI. The paper gives an overview of the topic, focusing agricultural p
The next figure gives a high-level overview of the sensor fusion algorithm. More details and explanations are provided in dedicated subsections. Data synchronization# ZED cameras, IMU, and GNSS are distinct sensors operating at different acquisition frequencies and timestamps. Fusing them requires dat...
overcomplex for a given training set but, at the same time, introducing mechanisms that prevent the algorithm from over-fitting. There are various ways to increase generalization ability of DL models (and avoid over-fitting), for example by means of regularization mechanisms (Kukacka et al.2017...
Fig. 1. A basic framework of the MOT algorithm [14]. (a) Object detection, (b) Feature extraction/motion prediction, (c) Similarity calculation, (d) Data association. (1) Object detection. The bounding box of the object in each input frame is obtained from the object detection algorithm...