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

BAIT

UWYOLOX: An Underwater Object Detection Framework Based on Image Enhancement and Semi-supervised Learch. However, the quality of underwater images obtained by optical imaging devices is poor and the available labeled data is lacking lead to lower mean Average Precision of underwater object detection. Therefore, in this paper, an novel underwater object detection framework, UWYOLOX, is proposed to

debunk

A Lightweight Sensor Fusion for Neural Visual Inertial Odometrymethods. However, all existing methods estimate each pose through visual and inertial measurements, which involves a large amount of computational redundancy, resulting in huge time costs and hardware damage when training and deploying on devices. In order to maintain accuracy while reducing the num

讽刺滑稽戏剧

A Two-Stage Framework for Kidney Segmentation in Ultrasound Images such as high noise, heterogeneous structure, low contrast, multiple artifacts, and relatively fixed shape, accurately segmenting clear and complete kidney structures from the images is still a challenging task. Our framework consists of two parts: shape aware dual-task multi-scale fusion network an

Introvert

Applicability Method for Identification of Power Inspection Evidence in Multiple Business Scenarioses, YOLOv3 retraining optimization and network compression are used to improve the scope of application, to meet the needs of power inspection evidence identification in multiple business scenarios. Firstly, to avoid insufficient model training due to small sample size, the Transformer model based o

GROSS

A Deep Learning Algorithm for Synthesizing Magnetic Resonance Images from Spine Computed Tomography nd MR images. The proposed algorithm utilizes a mixed loss function with three components to synthesize high-quality MR images from human spine CT images. The loss of structural consistency aims to enhance the structural perception of images and maintain consistency between the converted and origina

领导权

Investigating the Transferability of YOLOv5-Based Water Surface Object Detection Model in Maritime Ating and ocean conditions, advancements in this field are necessary. In this paper, we investigate the transferability of YOLOv5-based water surface object detection models in cross-domain scenarios. The evaluation is based on publicly available datasets and two newly proposed datasets, Taihu Trial

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持续

conflate

Multi-size Scaled CAM for More Accurate Visual Interpretation of CNNsty. These studies highlight regions of interest to image classification models by generating a saliency map that assign contribution values to each pixel in the input image. However, these current methods cannot accurately locate the key features of the target object and tend to include other irrele

prolate

Joint Attention Mechanism of YOLOv5s for Coke Oven Smoke and Fire Recognition Algorithmke and fire recognition algorithm with joint attention mechanism. The algorithm takes YOLOv5s as the base network and adds the attention mechanism module in BackBone to make the network pay more attention to important features and improve the accuracy of target detection; in addition, this paper add