Titlebook: International Conference on Neural Computing for Advanced Applications; 4th International Co Haijun Zhang,Yinggen Ke,Yuanyuan Mu Conference

使人入神

HARD

deficiency

accessory

A Bughole Detection Approach for?Fair-Faced Concrete Based on?Improved YOLOv5 feature transmission during the backbone and head part of the model. This allows for the fusing of low-level and high-level features and improves the perception of the detection model on minor flaws. We also construct a dataset of fair-faced concrete surface bugholes and compare our modified YOLOv5

Odyssey

Flatus

A Lightweight Sensor Fusion for?Neural Visual Inertial Odometrys with the original input feature maps for adaptive feature correction. This method improves the sensitivity of the model to channel features and enables more accurate image localization. Experimental results show that our algorithm maintains accuracy with a 10. reduction in network parameters compa

ALIEN

A Two-Stage Framework for?Kidney Segmentation in?Ultrasound Images a pre-trained model. The second part uses an iterative aggregation strategy for the pre-trained model to optimize it and reduce the noise and other issues in the prediction results. Experimental results show that our algorithm framework outperforms several state-of-the-art methods on kidney ultraso

FIN

Applicability Method for Identification of Power Inspection Evidence in Multiple Business Scenariosnts have proved that the retrained deep YOLOv3 network recognition model has significantly improved the accuracy of recognizing power marketing inspection images. The shallow recognition model effectively improves the timeliness of recognition. Specifically, four types of businesses were selected to

Onerous

A Deep Learning Algorithm for Synthesizing Magnetic Resonance Images from Spine Computed Tomography method outperforms current main-stream algorithms in MAE and PSNR evaluation metrics. This approach provides a promising solution for generating high-quality MR images from CT images, which can benefit many applications in the field of medical imaging.

Mirage

Physical-Property Guided End-to-End Interactive Image Dehazing Networktion of haze maps for deep dehazing, we design a transmission map guided interactive attention (TMGIA) module to teach an end-to-end information interaction network via dual channel-wise and pixel-wise attention. This way can refine the intermediate features of end-to-end information interaction net