The conventional Close circuit television(CCTV)cameras-based surveillance and control systems require human resource *** all the criminal activities take place using weapons mostly a handheld gun,revolver,pistol,sword...
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The conventional Close circuit television(CCTV)cameras-based surveillance and control systems require human resource *** all the criminal activities take place using weapons mostly a handheld gun,revolver,pistol,swords ***,automatic weapons detection is a vital requirement now a *** current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–*** time datasets,from local surveillance department’s test sessions are used for model training and *** consist of local environment images and videos from different type and resolution cameras that minimize the *** research also contributes in the making of Efficient-Net that is experimented and results in a positive *** results are also been represented in graphs and in calculations for the representation of results during training and results after training are also shown to represent our research ***-Net algorithm gives better results than existing *** using Efficient-Net algorithms the accuracy achieved 98.12%when epochs increase as compared to other algorithms.
About 10% individuals with visual impairment also use wheelchair, which makes them difficult to ambulate into a room that can only be distinguished by text independently. One thing that could be a solution is to imple...
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ISBN:
(数字)9798350381764
ISBN:
(纸本)9798350381771
About 10% individuals with visual impairment also use wheelchair, which makes them difficult to ambulate into a room that can only be distinguished by text independently. One thing that could be a solution is to implement a room nameplate recognition system on autonomous smart wheelchairs so that it can ambulate the user to the dedicated room autonomously. We proposed a lightweight YOLOv5-based method to detect room nameplates that is more suitable for embedded devices such as smart wheelchair. We improved YOLOv5 with ghost module and coordinate attention to reduce model complexity while still maintain the detection accuracy. Using room nameplate images data that has been collected by our self, the proposed method has 29 % less parameter with about the same accuracy as the original YOLOv5. With a low complexity of object detection model, our study may be utilized for room nameplate recognition system on smart wheelchair.
In past research on self-supervised learning for image classification, the use of rotation as an augmentation has been common. However, relying solely on rotation as a self-supervised transformation can limit the abil...
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ISBN:
(数字)9798350354096
ISBN:
(纸本)9798350354102
In past research on self-supervised learning for image classification, the use of rotation as an augmentation has been common. However, relying solely on rotation as a self-supervised transformation can limit the ability of the model to learn rich features from the data. In this paper, we propose a novel approach to self-supervised learning for image classification using several localizable augmentations with the combination of the gating method. Our approach uses flip and shuffle channel augmentations in addition to the rotation, allowing the model to learn rich features from the data. Furthermore, the gated mixture network is used to weigh the effects of each self-supervised learning on the loss function, allowing the model to focus on the most relevant transformations for classification.
This tertiary systematic literature review examines 29 systematic literature reviews and surveys in Explainable Artificial Intelligence (XAI) to uncover trends, limitations, and future directions. The study explores c...
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ISBN:
(数字)9798350382501
ISBN:
(纸本)9798350382518
This tertiary systematic literature review examines 29 systematic literature reviews and surveys in Explainable Artificial Intelligence (XAI) to uncover trends, limitations, and future directions. The study explores current explanation techniques, providing insights for researchers, practitioners, and policymakers interested in enhancing AI transparency. Notably, the increasing number of systematic literature reviews (SLRs) in XAI publications indicates a growing interest in the field. The review offers an annotated catalogue for human-computer interaction-focused XAI stakeholders, emphasising practitioner guidelines. Automated searches across ACM, IEEE, and science Direct databases identified SLRs published between 2019 and May 2023, covering diverse application domains and topics. While adhering to methodological guidelines, the SLRs often lack primary study quality assessments. The review highlights ongoing challenges and future opportunities related to XAI evaluation standardisation, its impact on users, and interdisciplinary research on ethics and GDPR aspects. The 29 SLRs, analysing over two thousand papers, include five directly relevant to practitioners. Additionally, references from the SLRs were analysed to compile a list of frequently cited papers, serving as recommended foundational readings for newcomers to the field.
Sasirangan cloth is one of the traditional cloths owned by Indonesia and is a typical cloth originating from the province of South Kalimantan. This Sasirangan cloth has many motifs and is unique. Sasirangan cloth is a...
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Facial palsy is a condition characterized by facial paralysis, affecting the patient's motor function. Detection is typically done through a clinical expert's direct observation of facial muscles. However, man...
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Cervical cancer is one of the most common causes of death among women worldwide. However, this fatal disease can be treated, and the mortality rate can be decreased if detected at an early stage. The Papanicolaou test...
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Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot ***,recognizing actions from such videos ...
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Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot ***,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera *** research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)*** first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale *** YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further *** joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are *** features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity ***-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing *** particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.
In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company's busin...
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This paper presents an all-encompassing exploration on the conception and implementation of sturdy and impregnable decentralized autonomous organizations (DAOs) custom-made for the Metaverse, capitalizing on the capab...
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