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The study of stereo matching optimization based on multi-baseline trinocular model
The huge computational complexity, occlusion and low texture region problems make stereo matching a big challenge. In this work, we use …
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A Study of General Data Improvement for Large-Angle Head Pose Estimation
Predicting Euler angles of head pose using end-to-end CNN from a single RGB image is a popular application in recent years. However, …
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Omnidirectional stereo depth estimation based on spherical deep network
Omnidirectional depth estimation is an emerging research topic and has received significant attention in recent years. However, the …
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Pyramid Feature Attention Network for Monocular Depth Prediction
Deep convolutional neural networks (DCNNs) have achieved great success in monocular depth estimation (MDE). However, few existing works …
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A Discussion of Optimization about Stereo Image Depth Estimation Based on Multi-baseline Trinocular Camera Model
The huge computational complexity and occlusion problems make stereo matching a major challenge. In this work, we use multi-baseline …
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A Shadow Detection Method for Retaining Key Objects in Complex Scenes
The existing shadow detection methods have achieved good results on standard shadow datasets such as SBU and UCF. However, in actual …
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A Review on Quantitative Analyzing Axonal Transport of Mitochondria
The movements of mitochondrial are especially critical for neuronal growth and function. However, to analyze and quantify this process …
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Pixel-level Diabetic Retinopathy Lesion Detection Using Multi-scale Convolutional Neural Network
Diabetic retinopathy (DR) is one of the leading causes of preventable blindness. It’s urgent to develop reliable methods for auto …
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Depth-based removal of thermal reflection with the light-field theory
Thermal imaging is a useful imaging technique in many scenarios. It can capture the temperature distribution of scenes in the dark and …
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Image Processing: Facilitating Retinanet for Detecting Small Objects
Detecting small objects is a challenging task in object detection due to low spatial resolution and interference by background. …
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