(2021) designed a lightweight network backbone based on a novel spatial attention mechanism and transfer learning to classify garbage images, and achieved good results in the garbage classification task on Huawei cloud platform with an accuracy of 96.17% and about 450M FLOPs(floating-point ...
According to the actual work of the sweeper and the real-time classification of garbage images, the single-stage YOLO v5s object detection algorithm is used to classify and identify the target garbage in the road surface images, and the algorithm structure is shown in Fig. 2. Fig. 2 Road ...
Finally, classify and regress the candidate regions. Its main representative detection algorithms include Faster RCNN2 and Mask RCNN3. In 2016, Ren et al.2 proposed the Fast RCNN detection algorithm, which has higher detection accuracy, especially for small object detection, and has higher ...
Our approach is to use computer vision technique to classify the garbage based on its severity. For this we have rated garbage on a scale of 1 to 5 with 5 as cleanest and 1 as the dirtiest. To achieve our aim, we have used Faster-RCNN Inception v2 model, and have procured an ...
Finally, classify and regress the candidate regions. Its main representative detection algorithms include Faster RCNN2 and Mask RCNN3. In 2016, Ren et al.2 proposed the Fast RCNN detection algorithm, which has higher detection accuracy, especially for small object detection, and has ...