Xiao-Chen Bo Disease genes data source and number of genes selected CMTCN curated cancer-related genes/miRNAs manually for 33 types of cancer by referring to cancer gene/miRNA databases. It later went on national broadcast and aired on Hubei TV on January 26, 2020. Love and Destiny (Chinese: 宸汐缘; pinyin: Chen Xi Yuan) is a 2019 Chinese television series starring Chang Chen and Ni Ni. This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile. The first concept is to apply D. Tax's one-class classifier as a steerable descriptor of such a complex volumetric structure. However, conventional motion detection techniques often suffer from the loss of moving objects due to bit-rate variation in video streams transmitted via wireless video communication systems. Join Facebook to connect with Bo-Hao Chen and others you may know. This paper proposes a novel video stabilization approach that is based on the shortest spanning path clustering algorithm for effective and reliable estimation of t... Haze removal is an important image restoration technology that aims to remove annoying haze particles from images. In such situations, traditional visibility restoration approaches usually cannot adequately restore images due to poor estimation of haze thickness and the persistence of color cast problems. It then utilizes DCT-based spa... Due to the problems of power-hungry displays and limited battery life in electronic devices, the concept of “green computing,” which entails a reduction in power consumption, is proposed. Department of Computer Science and Engineering, Two-Pass Bilateral Smooth Filtering for Remote Sensing Imagery, Single Image Glare Removal Using Deep Convolutional Networks, Deep Prior Guided Network For High-Quality Image Fusion, Itinerary Planning via Deep Reinforcement Learning, Restoration of Images With High-Density Impulsive Noise Based on Sparse Approximation and Ant-Colony Optimization, Deep Battery Saver: End-to-end Learning for Power Constrained Contrast Enhancement, Single Image Snow Removal Using Sparse Representation and Particle Swarm Optimizer, Driver Danger-Level Monitoring System Using Multi-Sourced Big Driving Data, Towards Perspective-Free Pavement Distress Detection via Deep Learning, Smoke 100k: A Database for Smoke Detection, Building an UAV anti-collision system with low-power FM ranging radar and camera image, An Efficient Single Image Enhancement Approach using Luminance Perception Transformation, Towards Unsupervised Single Image Dehazing With Deep Learning, Power-Constrained Image Contrast Enhancement Through Sparse Representation by Joint Mixed-Norm Regularization, Color Transferred Convolutional Neural Networks for Image Dehazing, A Grey Relational Analysis-Based Motion Detection Algorithm for Real-World Surveillance Sensor Deployment, An Advanced Driver Risk Measurement System for Usage-Based Insurance on Big Driving Data, Easy3D: A Holographic Advertising Platform, An Advanced Deep Framework for Recognition of Distracted Driving Behaviors, Accurate Emotion Recognition for Driving Risk Prevention in Driver Monitoring System, Near-Threshold CORDIC Design with Dynamic Circuitry for Long-Standby IoT Applications, Saliency-Guided Deep Framework for Power Consumption Suppressing on Mobile Devices, A Robust Moving Object Detection in Multi-Scenario Big Data for Video Surveillance, Power Constrained Contrast Enhancement by Joint L2,1-norm Regularized Sparse Coding for OLED Display, Impaired driving detection based on deep convolutional neural network using multimodal sensor data, Highly Accurate Image Reconstruction for Multimodal Noise Suppression Using Semisupervised Learning on Big Data, Removing Haze Particles From Single Image via Exponential Inference With Support Vector Data Description, A Fast Image Contrast Enhancement Algorithm Using Entropy-Preserving Mapping Prior, Traffic Collision Detection Using Crowd Voting, Automatic Dangerous Driving Intensity Analysis for Advanced Driver Assistance Systems From Multimodal Driving Signals, Haze Removal Using Radial Basis Function Networks for Visibility Restoration Applications, Error-Optimized Sparse Representation for Single Image Rain Removal, Counter-Propagation Artificial Neural Network-based Motion Detection Algorithm for Static-Camera Surveillance Scenarios, An entropy-preserving histogram modification algorithm for image contrast enhancement, Image Noise Removing Using Semi-supervised Learning on Big Image Data, Low-Rank Representation with Contextual Regularization for Moving Object Detection in Big Surveillance Video Data, Eliminating Driving Distractions: Human-Computer Interaction with Built-In Applications, Denoising Using Inverse-Distance Weighting with Sparse Approximation, Improved global motion estimation via motion vector clustering for video stabilization, Edge Collapse-Based Dehazing Algorithm for Visibility Restoration in Real Scenes, A High-Efficiency and High-Speed Gain Intervention Refinement Filter for Haze Removal, A Hybrid Background Subtraction Method with Background and Foreground Candidates Detection, Integral non-local means algorithm for image noise suppression, Hazy Image Restoration by Bi-Histogram Modification, An Advanced Single-Image Visibility Restoration Algorithm for Real-World Hazy Scenes, Probabilistic neural networks based moving vehicles extraction algorithm for intelligent traffic surveillance systems, A Morphological Mean Filter for Impulse Noise Removal, A background model re-initialization method based on sudden luminance change detection, Visibility Restoration of Single Hazy Images Captured in Real-World Weather Conditions, An Efficient Visibility Enhancement Algorithm for Road Scenes Captured by Intelligent Transportation Systems, Parametric Representation of Objects in Color Space Using One-Class Classifiers, High safety vehicular transportation system and operational method thereof, Automatic Moving Object Extraction Through a Real-World Variable-Bandwidth Network for Traffic Monitoring Systems, Accurate Detection of Moving Objects in Traffic Video Streams over Limited Bandwidth Networks, Improved Visibility of Single Hazy Images Captured in Inclement Weather Conditions, Highly Accurate Moving Object Detection in Variable Bit Rate Video-Based Traffic Monitoring Systems, Visibility Enhancement of Single Hazy Images Using Hybrid Dark Channel Prior, A Novel Visibility Restoration Algorithm for Single Hazy Images, An automatic motion detection algorithm for transport monitoring systems, Enhanced extraction of moving objects in variable bit-rate video streams, A novel moving vehicles extraction algorithm over wireless internet, Single Image Dehazing with Optimal Color Channels and Nonlinear Transformation, Blue Channel and Fusion for Sandstorm Image Enhancement, Image dehazing using window-based integrated means filter, A Contrast-Guided Approach for the Enhancement of Low-Lighting Underwater Images, Integration of new moving object segmentation and classification techniques using optimal salp swarm-based feature fusion with linear multi k-SVM classifier, Optimal feed forward neural network based automatic moving vehicle detection system in traffic surveillance system, Hourly wind speed forecasting based on Support Vector Machine and Artificial Neural Networks, Driver Fatigue Detection Systems Using Multi-Sensors, Smartphone, and Cloud-Based Computing Platforms: A Comparative Analysis, An adaptive background modeling for foreground detection using spatio-temporal features, Computing in Mathematics, Natural Science, Engineering and Medicine. All Professional Baseball Statistics for Bo-Hao Chen. Congs Hao Zhang, Jinwei Wan, Chaojie Wang and Long Tian! Shi-Ting Ye received, Oct. 2020: Congratulations to Shi-Ting Ye for winning the Honorable Mention in, Oct. 2020: Congratulations to Lily Yin for winning the Merit Award in. Automated detection of moving objects is an essential task for any intelligent transportation system. The proposed method first uses the inverse-distance weighting-based prediction to estimate noise-recovered pixels. ... Video analysis and understanding is an active area of research in the field of computer vision. The user module stores and provides carpool data, stores and provides states of individual carpool car, submits a carpool request and comprises a save our soul (SOS) system. I am an Associate Professor in the Department of Computer Science and Engineering at Yuan Ze University. However, these filters inevitably induce enormous computational burden while... Background subtraction for motion detection is often used in video surveillance systems. Overall: A River Runs Through It is a Chinese Romance, Drama (2020). RECOMMENDED. To detect foreground object or moving object in a scene accurately, foreground detection method serves as a basic step in many computer vision applications like visual surveillance [1,19,25,30,40,47,54,63], human-machine interaction [33,52,56,59], object tracking [22,28,34], vision-based hand gesture recognition [48], person counting [29,38], traffic surveillance [12,17,23, IEEE Transactions on Circuits and Systems for Video Technology (5), IEEE Transactions on Industrial Electronics (3), ACM Transactions on Intelligent Systems and Technology (3). Join ResearchGate to find the people and research you need to help your work. Median filtering computation for noise removal is often used in impulse noise removal techniques, but the difficulties in removing high-density noise aspect restrict its development. To solve this problem, a... Visibility restoration techniques are widely used for information recovery of hazy images in many computer vision applications. (Disclaimer: This search is powered by PubMed, a service of the U.S. National Library of Medicine. Sudden changes in illumination often occur in real world scenarios and may cause considerable difficulties in modeling backgrounds for the state-of-the-art background subtraction methods. First, the image is transformed by the proposed Luminance Perception procedure from the spa... Power-constrained image contrast enhancement is a fundamental step for improving the battery life of modern consumer devices with embedded emissive-display panels, such as organic light-emitting diodes (OLEDs). Moreover, danger-level analysis is vital for automotive safety systems and driving assistance applications. Hao Ming Chen received his B.Sc, and M.Sc from National Taiwan University in 2002 and 2004, and his Ph.D. in Chemistry from National Taiwan University in 2008, and then was a postdoctoral fellow at Department of Chemistry and Physics in National Taiwan University. However, the efficacies of traditional dehazing methods are easily hindered by insufficient estimation of haze thickness, and thus cannot effectively provide satisfactory haze removal results. A personalized automobile insurance mechanism presents challenges that are different from those presented by the general driving behaviors analyzed by driver assistance applications. This article proposes a novel smart car demonstration platform, with a focus on the intuitive paradigm of human?computer interaction (HCI). However, images recovered through conventional image dehazing methods that use either haze-relevant priors or heuristic cues to estimate transmission maps may not lead to sufficiently accurate haze removal from single images. Different strategies or mechanisms have been used to eliminate the brute-force computation in bilateral filters. Breast cancer (BC) is the second leading cause of cancer-related death among women worldwide. It was first aired on Astro Wah Lai Toi in Malaysia in 2012. Bo Zhang, Hongyu Zhang, Junjie Chen, Dan Hao, Pablo Moscato In: The 35th IEEE International Conference on Software Maintenance and Evolution, September 30-October 4, 2019, pages to appear, Cleveland, Ohio, USA [FSE'19] Compiler Bug Isolation via Effective Witness Test … I direct the Multimedia BigData System (BigMMS) Lab. Outdoor images captured during haze weather conditions generally exhibit visibility degradation. There is increasing demand for an ADAS framework that can increase driving safety by detecting dangerous driving behavior from driver, vehicle, and lane attributes. Siu-Ho Chin, Actor: Tai gik Cheung Sam Fung. The visibility of outdoor images captured in inclement weather will become degraded due to the presence of haze, fog, mist, and so on. Siu-Ho Chin was born on January 26, 1963 in Hong Kong. In this paper, we propose a simple and effective background re-initialization method that detects sudden luminance change effectively. Tang Chen was the predecessor Clear Sky Douluo to Tang Hao and the former Clear Sky Clan Head during its unrivaled rise to a top sect. Site Last Updated: Friday, March 6, 9:26AM Question, Comment, Feedback, or … In poor weather conditions, s cf (j ) is assumed to be free from λ and t ∈ [0, 1], ... Specifying a single patch size for images with possibly complex and heterogeneous content might lead to a non-ideal fit for their different regions. I am actively looking for motivated students to join my group! A rate control scheme produces variable bit rate video streams to match the available network bandwidth. Chen Hao is the Chairman, Legal Representative of Zhuhai Yilian New Energy Motors Co., Ltd., a wholly-owned subsidiary of China Titans Energy Technology Group Co., Ltd.He graduated from Peking University in 1996, majoring in international economics. The dark channel prior has been considered to be an efficient dehazing technique in recent years. © 2008-2021 ResearchGate GmbH. To achieve motion detection that is both reliable and ac... Haze removal is the process by which horizontal obscuration is eliminated from hazy images captured during inclement weather. Mater. Intelligent vehicles use advanced driver assistance systems (ADASs) to mitigate driving risks. Generally students doing research in the BigMMS lab will be expected to commit significant time (40+ hours per week) to their project. Bidirectional Recurrent Neural Networks with Adversarial Training (BIRNAT) This repository contains the code for the paper BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging (The European Conference on Computer Vision 2020) by Ziheng Cheng, Ruiying Lu, Zhengjue Wang, Hao Zhang, Bo Chen, Ziyi Meng and Xin Yuan. Image dehazing is a crucial image processing step for outdoor vision systems. Drivers often turn on the headlights of their vehicles and streetlights are often activated, resulting in localized light sources in images capturing road scenes in these conditions. He is known for his work on Tai-Chi Master (1993), Fist of Legend … Estimation of haze density is an essential task of visibility restoration techniques. With the Department of Computer Science and Engineering at Yuan Ze University increase the quality of edge-preserving image smoothing achieved... 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