The embracement of the wireless technology by the automobile industry has led to novel research interests in the field of Vehicular Ad-hoc Networks (VANETs). In addition to ad-hoc mode, a VANET supports infrastructure...
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The process of identifying and categorizing lung cancer in its early stages is difficult, yet doing so will improve patient survival rates. There is a wealth of research that segments and categorizes lung nodules usin...
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As sports grow in popularity need for effective online turf booking applications has also increased. Although some existing applications are faced with numerous challenges such as;restrictions on access, ineffectivene...
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The integration of Traffic Light Detection (TLD) systems with Advanced Emergency Braking Systems (AEBS) marks a critical milestone in enhancing road safety and paving the way for advanced autonomous driving. This surv...
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ISBN:
(纸本)9789819783540
The integration of Traffic Light Detection (TLD) systems with Advanced Emergency Braking Systems (AEBS) marks a critical milestone in enhancing road safety and paving the way for advanced autonomous driving. This survey paper provides a panoramic and extensive overview of the state-of-the-art TLD solutions leveraging sensors and deep learning techniques. With an increasing emphasis on accident prevention and traffic management, the intersection of TLD and AEBS has become a focal point of research and development. This survey begins by elucidating the fundamental challenges associated with TLD, including varying environmental conditions, occlusions, and complex traffic scenarios. We explore the pivotal role of sensors such as cameras, LiDAR, and radar in providing the requisite data for TLD, and delve into the intricacies of sensor fusion techniques for enhanced perception. Deep Learning has emerged as a cornerstone technology in TLD, enabling robust object detection, classification, and real-time decision-making. We meticulously analyze a spectrum of deep learning architectures including Single-Shot Detectors (SSD), Faster R-CNN, YOLO, and custom-designed networks tailored for TLD applications. Furthermore, the survey examines critical components of the TLD pipeline, encompassing data collection, preprocessing, model training, real-time inference, and integration with AEBS. Emphasis is placed on real-time constraints, multi-modal sensor fusion, and adaptability to diverse traffic light configurations. The paper also delves into the significance of accurate traffic light state prediction, going beyond mere detection to anticipate traffic light changes and optimize vehicle control actions. Human-centric interaction and privacy concerns are addressed, encompassing driver warnings, user interfaces, and data anonymization strategies. Moreover, the survey discusses the importance of safety, validation, and collaboration within the TLD and AEBS ecosystem, emphasizing compl
Diabetic retinopathy (DR) is a complication of diabetes that causes retinal changes that affect vision. If not caught early, it can lead to blindness. Unfortunately, DR is not a reversible process where treatment only...
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作者：
Huang, Po-HsunHsiao, Tzu-Chien
Hsinchu300 Taiwan Nycu
Department of Computer Science College of Cs and Institute of Biomedical Engineering College of Electrical and Computer Engineering Hsinchu300 Taiwan
The determination of appropriate parameters and an appropriate window size in most entropy-based measurements of time-series complexity is a challenging problem. Inappropriate settings can lead to the loss of intrinsi...
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Kidney disease (KD) is a gradually increasing global health concern. It is a chronic illness linked to higher rates of morbidity and mortality, a higher risk of cardiovascular disease and numerous other illnesses, and...
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Optical character recognition is a way of converting scanned images of printed or handwritten documents into machine-encoded text, making it easier to store, browse, retrieve, and process electronic data. In this rese...
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In a world where microblogging has become an integral part of modern life., the sudden outbreak of COVID-19 swiftly infiltrated public opinion on various social networking platforms. With individuals adhering to socia...
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The tremendous development of cloud computing with related technol-ogies is an unexpected ***,centralized cloud storage faces few chal-lenges such as latency,storage,and packet drop in the *** storage gets more attent...
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The tremendous development of cloud computing with related technol-ogies is an unexpected ***,centralized cloud storage faces few chal-lenges such as latency,storage,and packet drop in the *** storage gets more attention due to its huge data storage and ensures the security of secret *** of the developments in cloud storage have been positive except better cost model and effectiveness,but still data leakage in security are billion-dollar questions to *** data security techniques are usually based on cryptographic methods,but these approaches may not be able to with-stand an attack from the cloud server's ***,we suggest a model called multi-layer storage(MLS)based on security using elliptical curve cryptography(ECC).The suggested model focuses on the significance of cloud storage along with data protection and removing duplicates at the initial *** on divide and combine methodologies,the data are divided into three ***,thefirst two portions of data are stored in the local system and fog nodes to secure the data using the encoding and decoding *** other part of the encrypted data is saved in the *** viability of our model has been tested by research in terms of safety measures and test evaluation,and it is truly a powerful comple-ment to existing methods in cloud storage.
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