The consumer demand for retrieving and delivering visual content through consumer electronic devices has increased rapidly in recent years. The quality of video in packet networks is susceptible to certain traffic characteristics: average bandwidth a...
When we couple the rise in video streaming with the growing number of portable devices (smart phones, tablets, laptops), we see an ever-increasing demand for high-definition video online while on the move. Wireless networks are inherently characteris...
Dynamic Adaptive Streaming over HTTP (DASH) offers adaptive and dynamic multimedia streaming solutions to heterogeneous end systems. However, it still faces many challenges in determining an appropriate rate adaptation technique to provide the best q...
Multimedia video streaming, identified as the dominant internet data consumption service, brings forth challenges in consistently delivering optimal video quality. Dynamic Adaptive Streaming over HTTP (DASH), while prevalent, often encounters bufferi...
Edge computing is the best approach for meeting the exponential demand and the real-time requirements of many video analytics applications. Since most of the recent advances regarding the extraction of information from images and video rely on comput...
A wireless network gives flexibility to the user in terms of mobility that attracts the user to use wireless communication more. The video communication in the wireless network experiences Quality of Services (QoS) and Quality of Experience (QoE) iss...
In the recent past, the number of surveillance cameras placed in the public has increased significantly, and an enormous amount of visual data is produced at an alarming rate. Resultantly, there is a demand for a distributed system for video analytic...
The recent advancements of wireless technology and applications make downlink scheduling and resource allocations an important research topic. In this paper, we consider the problem of downlink scheduling for multi-user scalable video streaming over...
Deep learning models have significantly improved object detection, which is essential for visual sensing. However, their increasing complexity results in higher latency and resource consumption, making real-time object detection challenging. In order...
360-degree video streaming for high-quality virtual reality (VR) is challenging for current wireless systems because of the huge bandwidth it requires. However, millimeter wave (mmWave) communications in the 60 GHz band has gained considerable intere...
Video streaming solutions have increased their importance in the last decade, enabling video on demand (VoD) services. Among several innovative services, 5G and Beyond 5G (B5G) systems consider the possibility of providing VoD-based solutions for sur...
In recent years, the amount of intelligent CCTV cameras installed in public places for surveillance has increased enormously and as a result, a large amount of video data is produced every moment. Due to this situation, there is an increasing request...
As the deployment of CCTV cameras for safety continues to increase, the monitoring workload has significantly exceeded the capacity of the current workforce. To overcome this problem, intelligent CCTV technologies and server-efficient deep learning a...
The integration of the Scalable Service-Oriented Middleware over IP (SOME/IP) within Automotive Ethernet enables efficient, service-oriented communication in vehicles. This study presents a video stream transmission library using SOME/IP to transfer...
Due to influence of COVID-19, telemedicine is becoming more and more important. High-quality medical videos can provide a physician with a better visual experience and increase the accuracy of disease diagnosis, but this requires a dramatic increase...
The rapid growth in large-scale distributed video conferencing, remote education, and real-time broadcasting poses significant challenges to traditional centralized streaming systems, particularly regarding scalability, cost, and reliability under hi...
Real-time media streaming over publish–subscribe platforms is increasingly vital in scenarios that demand the scalability of event-driven architectures while ensuring timely media delivery. This is especially true in multi-modal and resource-co...
The exponential growth of video data across domains such as surveillance, transportation, and healthcare has raised critical challenges in scalability, real-time processing, and privacy preservation. While existing studies have addressed individual a...
As urban populations expand and congestion intensifies, traditional ground transportation struggles to satisfy escalating mobility demands. Unmanned Electric Vertical Take-Off and Landing (eVTOL) aircraft, as a key enabler of Urban Air Mobility (UAM)...
Visual surveillance systems have been playing a vital role in human modern life with a large number of applications, ranging from remote home management, public security to traffic monitoring. The recent High Efficiency Video Coding (HEVC) scalable e...
Dense video captioning is a critical task in video understanding, requiring precise temporal localization of events and the generation of detailed, contextually rich descriptions. However, the current state-of-the-art (SOTA) models face significant c...
This paper explores novel architectures for fast backprojection based video synthetic aperture radar (BP-VISAR) with multiple GPUs. The video SAR frame rate is analyzed for non-overlapped and overlapped aperture modes. For the parallelization of the...
Rapid advancements in peer-to-peer (P2P) streaming technologies have significantly impacted digital communication, enabling scalable, decentralized, and real-time content distribution. Despite these advancements, challenges persist, including dynamic...
Efficient human detection in video streams is essential for various IoT applications, including surveillance, smart cities, intelligent transportation systems (ITSs), and industrial automation. However, resource-constrained IoT devices often face lim...
This paper addresses the increasing demand for efficient and scalable streaming service applications within the context of edge computing, utilizing NVIDIA Jetson Xavier NX hardware and Docker. The study evaluates the performance of DeepStream and Si...
Generating accurate and contextually rich captions for images and videos is essential for various applications, from assistive technology to content recommendation. However, challenges such as maintaining temporal coherence in videos, reducing noise...
The rapid expansion of video conferencing and remote works due to the COVID-19 pandemic has resulted in a massive volume of video data to be analyzed in order to understand the audience engagement. However, analyzing this data efficiently, particular...
In the digital era, the demand for real-time streaming services highlights the scalability, data sovereignty, and privacy limitations of traditional centralized systems. VidBlock introduces a novel decentralized blockchain architecture that leverages...
This study proposes Dual-Stream Former, a novel architecture that integrates a Video Swin Transformer and Conformer designed to address the challenges of visual speech recognition (VSR). The model captures spatiotemporal dependencies, achieving a sta...
Internet service providers allocate network resources for different network flows. Among them, video streaming requires substantial network bandwidth to provide a satisfactory user experience. The identification of video traffic is one of the tools t...
Educational videos contain long periods of visual redundancy, where only a few frames convey meaningful instructional information. Conventional video models, which are designed for dynamic scenes, often fail to capture these subtle pedagogical transi...
Accurate and real-time classification of low-latency Internet traffic is critical for applications such as video conferencing, online gaming, financial trading, and autonomous systems, where millisecond-level delays can degrade user experience. Exist...
The rapid loss of biodiversity significantly impacts birds’ environments and behaviors, highlighting the importance of analyzing bird behavior for ecological insights. With the growing adoption of Machine Learning (ML) algorithms in the Interne...
Recently, as the amount of real-time video streaming data has increased, distributed parallel processing systems have rapidly evolved to process large-scale data. In addition, with an increase in the scale of computing resources constituting the dist...
Remote sensing video (RSV) provides continuous, high spatiotemporal earth observations that are increasingly important for environmental monitoring, disaster response, infrastructure inspection and urban management. Despite this potential, operationa...
In this era of big data, the amount of video content has dramatically increased with an exponential broadening of video streaming services. Hence, it has become very strenuous for end-users to search for their desired videos. Therefore, to attain an...
The analysis of dynamic remote sensing scenes from unmanned aerial vehicles (UAVs) is shifting from reactive processing to proactive, predictive intelligence. Central to this evolution is video prediction—forecasting future imagery from past ob...
In the context of the rapid development of edge computing, optimizing data transmission and reducing latency is crucial for efficient collaborative processing among edge servers. Traditional TCP/IP protocols are hindered by high latency and low throu...
Distributed appliances connected to the Internet have provided various multimedia services. In particular, networked Personal Video Recorders (PVRs) can store broadcast TV programs in their storage devices or receive them from central servers, enabli...
Underwater robotics produces diverse and complex streams of sensor, image, video, and navigational data under challenging environmental conditions, creating obstacles for seamless integration and interpretation. This paper introduces ROVON (Remotely...
In this paper, a real-time deep learning-based framework for detecting and tracking Unmanned Aerial Vehicles (UAVs) in video streams captured by a fixed-wing UAV is proposed. The proposed framework consists of two steps, namely intra-frame multi-UAV...
So far, existing sub-GHz wireless communication technologies focused on low-bandwidth, long-range communication with large numbers of constrained devices. Although these characteristics are fine for many Internet of Things (IoT) applications, more de...
MCJ2K (Motion-Compensated JPEG2000) is a video codec based on MCTF (Motion- Compensated Temporal Filtering) and J2K (JPEG2000). MCTF analyzes a sequence of images, generating a collection of temporal sub-bands, which are compressed with J2K. The R/D...
Forest fires in Yanyuan County, a typical dry-hot valley region, pose serious threats to ecological security and public safety. Conventional fire warning methods rely heavily on manual surveys, making them time-consuming, labor-intensive, and prone t...
The increasing demand for high-speed, reliable, and fair network services in multi-gigabit-wide area networks (WANs) has necessitated the development of advanced bandwidth allocation mechanisms. This paper proposes a Fair and QoS-Aware Dynamic Bandwi...
Snow accumulation on photovoltaic (PV) panels can cause significant energy losses in cold climates. While drone-based monitoring offers a scalable solution, real-world challenges like varying illumination can hinder accurate snow detection. We previo...
Accurate river flow velocity estimation is critical for flood risk management and sediment transport modeling. This study proposes an artificial intelligence (AI)-based framework that integrates optical flow analysis and deep learning to estimate flo...
Vehicle re-identification (re-ID) across disparate sensing modalities remains a fundamental challenge for transportation research. In this work, we introduce a deep multi-view vehicle re-ID framework that leverages Siamese networks to compare pairs o...
In future mobile networks, the evolution of optical transport architectures enabling the flexible, scalable interconnection of Baseband Units (BBUs) and Radio Units (RUs) with heterogeneous interfaces is a significant issue. In this paper, we propose...
Fabric defect detection is essential for quality assurance in textile manufacturing, where manual inspection is inefficient and error-prone. This paper presents a real-time deep learning-based system leveraging YOLOv11 for detecting defects such as h...
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