Since there are very few datasets available for underwater objects, in this paper, an Extended Underwater Object Detection dataset with 16 object categories (EUWOD-16) was constructed. This was achieved by building a new annotated dataset consisting of divers, artifacts and various marine species,...
3.使用Union Dataset Augmentation(UDA)进行训练集的数据增强:采用了Minimal Color Loss和Locally Adaptive Contrast Enhancement(MLLE)图像增强方法对训练集进行了Union Dataset Augmentation(UDA),并将结果作为输入用于改进的YOLOv5框架。 传统方法 早期的传统检测方法主要提取颜色、纹理和几何形状等特征。 深度学习 随着深度...
To promote the development of underwater robot picking in sea farms, we propose an underwater open-sea farm object detection dataset called UDD. Concretely, UDD consists of 3 categories (seacucumber, seaurchin, and scallop) with 2227 images. To the best of our knowledge, it's the first data...
Underwater Object Detection and Pose Estimation using Deep Learning This paper presents an approach for making a dataset using a 3D CAD model for deep learning based underwater object detection and pose estimation. We also ... MH Jeon,Y Lee,YS Shin,... - Ifac Conference on Control Applicatio...
import ppdet from source directory without installing, run 'python setup.py install' to install ppdet firstly [05/07 12:46:39] ppdet.data.source.voc WARNING: Found an invalid bbox in annotations: xml_file: PaddleDetection/dataset/underwater/Annotations/005523.xml, x1: 2539.0, y1: 1396.0, ...
Oct 27, 2023 README Image Enhancement, Color Correction/Restoration RGB-D: Monocular Depth Estimation SESR: Simultaneous Enhancement and Super-Resolution SOD: Salient Object Detection Object Detection/Classification Moorea corals (UCSD):Data,Paper. ...
By substituting the Complete Intersection Over Union (CIOU) with WIOU, we increase penalties for low-quality samples, mitigating the effect of camouflaged information on detection. Our model achieved a MAP_0.75 of 72.5% on the Real-World Underwater Object Detection (RUOD) dataset, surpassing the...
SequenceFile Dataset The SequenceFile dataset contains a binary representation of the visualized raw acoustic data. As the raw DIDSON data represent sets of readings of the acoustic array at a particular time, it must be converted to pixel intensities on a Cartesian plane to form an image and sev...
State-of-the-art detection models were employed to test their performance (AP is the average precision) pertained on the COCO [1] dataset, as shown below in Figure 12. Figure 12. MS COCO object detection from [5]. The benchmarks provided in [5] show that YOLOv7 can effectively ...
All the YOLOv6 models have been pre-trained on the COCO object detection dataset. You can find the pre-trained weights on the official GitHub repository. There is also a YOLOv6 Large model trained with the ReLU activation [1], which tends to be faster but with a slightly lower mAP (51.7...