Titlebook: Image and Graphics Technologies and Applications; 18th Chinese Confere Wang Yongtian,Wu Lifang Conference proceedings 2023 The Editor(s) (i

剧本

音乐戏剧

CPML: Category Probability Mask Learning for Fine-Grained Visual Classificationoning that we only use global branch at test stage because the global feature is already regularized by the part features with CPML and CCL in training steps. Compared with current state-of-the-art methods, our methods achieve promising performance on three widely used FGVC datasets.

Medley

记成蚂蚁

AVID

A Self-supervised Learning Reconstruction Algorithm with an Encoder-Decoder Architecture for Diffusend diagnosis. However, the conventional image reconstruction algorithm in DOT is time-consuming and easy to error when recovering the distribution of optical parameters within the complete tissue. In this paper, we present an end-to-end reconstruction algorithm for DOT based on a deep convolutional

连锁,连串

TSR-Net: A Two-Step Reconstruction Approach for Cherenkov-Excited Luminescence Scanned Tomography reconstructing the distribution of the quantum field from boundary measurements is a typical ill-posed problem. In this work, we propose a novel two-step reconstruction network (TSR-Net) based on a fusion mechanism, that integrates two encoder-decoder networks (ED-Net) using a concatenation block.

Jingoism

A Method for Enhancing the Quality of Compressed Videos Based on 2D Convolution and Aggregating Spatof high-frequency information and compression artifacts. Especially in the case of limited coding resources, the blurring of content edges and obvious compression distortion will have a negative impact on the subjective quality of the video. Therefore, there is an urgent need to build a quality enha

修改

Panther

责难

Visual SLAM Algorithm Based on Target Detection and Direct Geometric Constraints in Dynamic Environms on target detection and direct geometric constraints. The algorithm first obtains static feature points and possible dynamic feature points of the current frame using a YOLOV7 target detection network. It then judges the real dynamic target using the geometric change relationship between the edges