In this paper, vehicle detection and fine-grained classification are addressed using deep learning. To perform fine-grained classification with related complexities, local dataset THS-10 having high intraclass and low interclass variation is exclusively prepared. The dataset consists of 4250 vehicle ...
基于MobileNetV3的车辆和行人的多标签分类 点赞(0) 踩踩(0) 反馈 所需:1 积分 电信网络下载 TencentOS-tiny 2024-12-18 12:18:54 积分:1 qycms 2024-12-18 12:18:18 积分:1 WordGo 2024-12-18 12:09:52 积分:1 bookjs-eazy 2024-12-18 12:09:16 积分:1 ...
Vision based automatic road traffic density estimation for both stationary and free flowing traffic scenes, and vehicle classification using an ensemble pattern classifier The main novelty of this thesis is the development of a vision based vehicle detection algorithm that is capable of extracting vehicl...
Besides, the heads of localization and classification are also combined. This single-stage architecture results in quick inference time. Together with the other detectors based on MobileNet, this new strategy has brought the vision of edge devices ever close to existence. The concept behind YOLO is...
can be used to perform this task in a fast manner with effective results. We achieve a mean F1 score of 0.528 at an IoU of 50% on the task of detection and classification of different types of damages in real-world road images acquired using a smartphone camera and our average inference...
The recognition process of MA-MobileNetV2 is illustrated in Figure 7. Firstly, the input image goes through the backbone network to obtain the feature map. Then, the obtained feature map is weighted using the Mixed Attention Module. The weighted feature map is then fed into pooling layers and...
Mobilenetv2: Inverted residuals and linear bottlenecks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 18–23 June 2018; pp. 4510–4520. [Google Scholar] Lin, T.Y.; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan,...
Here we experimented with Tensorflow Object Detection API, using pretrained models on COCO dataset, such as: "ssd_inception_v2_coco" and "ssd_mobilenet_v2_coco":Testing the coco pretrained models without retraining on simulator images didn't lead to any success, since the simulated traffic ...
art methods with remarkable margins by using only point cloud as input. Road Damage Detection And Classification In Smartphone Captured Images Using Mask R-CNN, IEEE International Conference On Big Data Cup 2018(2018年IEEE国际大数据杯会议的道路损伤检测和分类挑战)...
Apart from this, we have benchmarked the results on the developed dataset using eight state-of-the-art pre-trained convolutional neural network (CNN) models, namely Xception, InceptionV3, DenseNet121, MobileNetV2, and VGG16, NasNetMobile, ResNet50 and ResNet152. Among these, the Xception, ...