Abdulmotaleb El Saddik

University of Ottawa · School of Electrical Engineering and Computer Science

We investigate and observe the behavior and performance of Large Language Model (LLM)‐backed chatbots in addressing misinformed prompts and questions with demographic information within the domains of Climate Change and Mental Health. Through a combination of quantitative and qualitative methods, we assess the chatbots' ability to discern the verac...

The recent development of generative art, a typical category of artificial intelligence-generated content (AIGC), is essentially beneficial for social good, which can help amateurs to create artwork and improve experts’ efficiency. However, some artists are opposed to generative art technologies due to the copyright infringement and influence of th...

In recent years, there has been a growing interest in leveraging the metaverse to enhance community engagement and healthcare. This paper provides a comprehensive examination of wearable devices and sensors utilized within immersive environments to improve well-being and healthcare outcomes. We categorize the healthcare application domains that emp...

We investigate and observe the behaviour and performance of Large Language Model (LLM)-backed chatbots in addressing misinformed prompts and questions with demographic information within the domains of Climate Change and Mental Health. Through a combination of quantitative and qualitative methods, we assess the chatbots’ ability to discern the vera...

Texture image generation has been studied for various applications, including gaming and entertainment. However, context-specific realistic texture generation for industrial applications, such as generating defect textures on railway components, remains unexplored. A mobile-friendly, LLM-based tool that generates fine-grained defect characteristics...

We investigate and observe the behaviour and performance of Large Language Model (LLM)-backed chatbots in addressing misinformed prompts and questions with demographic information within the domains of Climate Change and Mental Health. Through a combination of quantitative and qualitative methods, we assess the chatbots' ability to discern the vera...

Supervised RGBT (SRGBT) tracking tasks need both expensive and time-consuming annotations. Therefore, the implementation of Self-Supervised RGBT (SSRGBT) tracking methods has become increasingly important. Straightforward SSRGBT tracking methods use pseudo-labels for tracking, but inaccurate pseudo-labels can lead to object drift, which severely af...

Oriented object detection in remote sensing images is a challenging task due to objects being distributed in multi-orientation. Recently, end-to-end transformer-based methods have achieved success by eliminating the need for post-processing operators compared to traditional CNN-based methods. However, directly extending transformers to oriented obj...

This paper presents a comprehensive meta-review of the intersection between Brain-Computer Interface (BCI) technologies and the Metaverse, emphasizing the enhancement of immersive experiences through VR, AR, MR, XR, Digital Twin, and haptic interfaces. The study classifies BCI devices into wearable and non-wearable categories, with a focus on their...

A Digital Twin (DT) replicates objects, processes, or systems for real-time monitoring, simulation, and predictive maintenance. Recent advancements like Large Language Models (LLMs) have revolutionized traditional AI systems and offer immense potential when combined with DT in industrial applications such as railway defect inspection. Traditionally...

Over the last few years, 360video traffic on the network has grown significantly. A key challenge of 360video playback is ensuring a high quality of experience (QoE) with limited network bandwidth. Currently, most studies focus on tile-based adaptive bitrate (ABR) streaming based on single viewport prediction to reduce bandwidth consumption. Howeve...

Monocular scene flow estimation is a task that allows us to obtain 3D structure and 3D motion from consecutive monocular images. Previous monocular scene flow usually focused on the enhancement of image features and motion features directly while neglecting the utilization of motion features and image features in the decoder, which are equally cruc...

Harnessing the transparent blockchain user behavior data, we construct the Political Betting Leaning Score (PBLS) to measure political leanings based on betting within Web3 prediction markets. Focusing on Polymarket and starting from the 2024 U.S. Presidential Election, we synthesize behaviors over 15,000 addresses across 4,500 events and 8,500 mar...

Accurate defect detection is crucial for ensuring the trustworthiness of intelligent railway systems. Current approaches either rely on static ensembling of Convolutional Neural Networks (CNNs) or on single deep-learning CNN models. Traditional methods use a large volume of data to identify underlying patterns. However, training a new defect classi...

A key challenge of 360° VR video streaming is ensuring high quality with limited network bandwidth. Currently, most studies focus on tile-based adaptive bitrate streaming to reduce bandwidth consumption, where resources in network nodes are not fully utilized. This article proposes a tile-weighted rate-distortion (TWRD) packet scheduling optimizati...

Point cloud segmentation is essential for scene understanding, which provides advanced information for many applications, such as autonomous driving, robots, and virtual reality. To improve the accuracy and robustness of point cloud segmentation, many researchers have attempted to fuse camera images to complement the color and texture information....

Audio analysis is useful in many application scenarios. The state-of-the-art audio analysis approaches assume that the data distribution at training and deployment time will be the same. However, due to various real-life environmental factors, the data may encounter drift in its distribution or can encounter new classes in the late future. Thus, a...

Ultra-high-resolution aerial videos are becoming increasingly popular for enhancing surveillance capabilities in sparsely populated areas. However, analyzing human activities automatically, such as "who is doing what?" in these videos, is desirable to realize their surveillance potential. In contrast, atomic visual action detection has successfully...

Recent advancements in cognitive computing, through the integration of artificial intelligence (AI) techniques, have facilitated the development of intelligent cognitive systems (ICS). This benefits railway defect detection by enabling ICS to emulate human-like analysis of defect patterns in image data. Although visual defect classification based o...

Extended meta/uni/Verse (XV), also known as “Mersivity,” “Vironmentalism,” “Social XR,” “Physical metaverse,” etc., combines eXtended Reality (XR), eXtended Intelligence (XI), eXtended Being (XB), including Digital Twin, eXtended Economy (XE), and eXtended Society (XS) into a vision that covers a generally agreed metaverse scope while extending the...

In recent years, the task of person re-identification (ReID) has placed a critical demand on accurately describing image features. Attention mechanisms, particularly Transformer-like self-attention (TLSA), have gained favor among researchers due to their outstanding feature descriptive performance. However, due to their intricate structures, TLSA m...

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) has been dedicated to advancing multimedia research, fostering discoveries, innovations, and practical applications since 2005. The journal consistently publishes top-notch, original research in emerging fields through open submissions, calls for papers, special issue...

Widely adopted digital cameras and smartphones have generated a large number of videos, which have brought a tremendous workload to video editors. Recently, a variety of automatic/semi-automatic video editing methods have been proposed to tackle these issues in some specific areas. However, for the production of meeting recordings, the existing stu...

Unsupervised domain adaptation (UDA) aims to alleviate the domain shift by transferring knowledge learned from a labeled source dataset to an unlabeled target domain. Although UDA has seen promising progress recently, it requires access to data from both domains, making it problematic in source data-absent scenarios. In this article, we investigate...

Recent advancements in consumer electronics as well as imaging technology have generated abundant multimodal data for consumer-centric AI applications. Effective analysis and utilization of such heterogeneous data hold great potential for consumption decisions. Hence, effective analysis of multi-modal consumer-generated content is a prominent resea...

Monocular scene flow estimation is a task that allows us to obtain 3D structure and 3D motion from consecutive monocular images. Previous monocular scene flow usually focused on the enhancement of image features and motion features directly while neglecting the utilization of motion features and image features in the decoder, which are equally cruc...

Mental health disorder rates have increased in recent years. In this research, we aim to address the barriers of stigma, accessibility, and affordability in mental healthcare by designing and developing a dialogue system that analyses the mental status of individuals. Additionally, it gives them personalized feedback based on the severity of the me...

Emerging intelligent transportation system applications witnessed significantly different requirements and performance metrics (e.g., latency, reliability, and quality of experience). To meet the diverse requirements, one can use a convergence of the metaverse with vehicular networks at the network edge which offers proactive analysis and efficient...

Recently, smart contract, a code script that autonomously runs on blockchains, has facilitated numerous decentralized applications and accelerated the boost of the Web3 ecosystem. However, the current underutilization of smart contracts and a large number of duplicate smart contracts have caused significant challenges to blockchains. Considering th...

Metaverse aims to construct a large, unified, immersive, and shared digital realm by combining various technologies, namely XR (extended reality), blockchain, and digital twin, among others. This article explores the Metaverse from the perspective of multimedia communication by conducting and analyzing real-world experiments on four different Metav...

With the continuous evolution of networking technologies, multi-modal services that involve video, audio, and haptic contents are expected to become the dominant multimedia service in the near future. Edge caching is a key technology that can significantly reduce network load and content transmission latency, which is critical for the delivery of m...

The automation of surveillance systems, driven by the rapid development of computer vision technology, has significantly enhanced the analysis of surveillance videos, particularly in recognition of human activity, including behavior analysis and violence detection, thereby bolstering public and industrial security. Despite these advancements, detec...

On march 18, 2024, NVIDIA unveiled Project GR00T, a general-purpose multimodal generative AI model designed specifically for training humanoid robots. Preceding this event, Tesla's revealing of the Optimus Gen 2 humanoid robot on December 12, 2023, underscored the profound impact robotics is poised to have on reshaping various facets of our daily l...

Emotion recognition is one of the crucial topics in computer vision to efficiently recognize the expression of humans through faces. Recently, transformers have been recognized as a robust architecture, and many vision-based transformer models for emotion recognition have been proposed. The major drawback of such models is the high computational co...

Oriented object detection in remote sensing images is a challenging task due to objects being distributed in multi-orientation. Recently, end-to-end transformer-based methods have achieved success by eliminating the need for post-processing operators compared to traditional CNN-based methods. However, directly extending transformers to oriented obj...

This survey delves into the convergence of blockchain, Web 3.0 technologies, and the decentralized metaverse, analyzing their combined effects on virtual experiences. The study meticulously examines the decentralized metaverse’s architecture, intrinsic properties, and transformative potential. Central to our analysis is the role of blockchain techn...

These Recent statistics and studies indicate that losses resulting from insider threats far exceed those from external attacks. Consequently, many organizations are investing in or acquiring insider threat detection systems to mitigate internal risks. However, three critical challenges emerge: 1) Client data frequently manifests as isolated islands...

Growth in the metaverse has been significant in recent years, aided by the robust communication capacities of the 5G network. Moving into the 6G era, integrated sensing and communication (ISAC) services are regarded as a potential solution for controlling avatars in the metaverse, because ISAC can enable users to have all-pervasive sensing capabili...

In today’s data-driven world, quick access to scholarly info is vital. However, current academic search engines face challenges such as restricted text-based searching, uncertainties related to researcher names, absence of contact details, and lack of profile summaries. To mitigate these issues, we introduce ScholarFace, an innovative concept that...

How to design your classroom in Metaverse? 🤔

Multiaccess edge computing (MEC) is a promising solution to the computation-intensive, low-latency rendering tasks of the metaverse. However, how to optimally allocate limited communication and computation resources at the edge to a large number of users in the metaverse is quite challenging. In this article, we propose an adaptive edge resource al...

6G communication networks are expected to become an integral part of the infrastructure needed for developing a smart society in the future. Addressing the challenges on the road towards realizing 6G network requirements in terms of quality of service, user experience, and security, is therefore of utmost importance. The digital twin (DT) technolog...

The metaverse, as a rapidly evolving socio-technical phenomenon, exhibits significant potential across diverse domains by leveraging Web3 (a.k.a. Web 3.0) technologies such as blockchain, smart contracts, and non-fungible tokens (NFTs). This survey aims to provide a comprehensive overview of the Web3 metaverse from a human-centered perspective. We...

The task of Open-World Compositional Zero-Shot Learning (OW-CZSL) is to recognize novel state-object compositions in images from all possible compositions, where the novel compositions are absent during the training stage. The performance of conventional methods degrades significantly due to the large cardinality of possible compositions. Some rece...

Digital twins (DTs), defined as the virtual representation of a real-world entity or system, act as a mirror to provide a way to simulate, predict physical behaviors, and possibly control the real-world entity where applicable. Originating in the industry, advances in computing capacity and recent progress in artificial intelligence (AI)-based anal...