Saliency-based representation visualization (SRV) (e.g., Grad-CAM) is one of the most classical and widely adopted explainable artificial intelligence (XAI) methods for its simplicity and efficiency. It can be used to...
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Mobile edge computing aims to provide cloud-like services on edge servers located near Mobile Devices (MDs) with higher Quality of Service (QoS). However, the mobility of MDs makes it difficult to find a global optima...
Mobile edge computing aims to provide cloud-like services on edge servers located near Mobile Devices (MDs) with higher Quality of Service (QoS). However, the mobility of MDs makes it difficult to find a global optimal solution for the coupled service placement and request scheduling problem. To address these issues, we consider a three-tier MEC network with vertical and horizontal cooperation. Then we formulate the joint service placement and request scheduling problem in a mobile scenario with heterogeneous services and resource limits, and convert it into two Markov decision processes to decouple decisions across successive time slots. We propose a Cyclic Deep Q-network-based Service placement and Request scheduling (CDSR) framework to find a long-term optimal solution despite future information unavailability. Specifically, to solve the issue of enormous action space, we decompose the system agent and train them cyclically. Evaluation results demonstrates the effectiveness of our proposed CDSR on user-perceived QoS.
Noise in data appears to be inevitable in most realworld machine learning applications and would cause severe overfitting problems. Not only can data features contain noise, but labels are also prone to be noisy due t...
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In the realm of 6G wireless networks, the Consumer Internet of Things (CIoT) aims to revolutionize consumer electronics by integrating advanced technologies such as Artificial Intelligence (AI). As CIoT environments b...
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This study describes a broad endeavor to use cutting-edge technologies to empower deaf primary school students in Sri Lanka. Three key elements make up the study: a sound recognition and classification system, an Andr...
This study describes a broad endeavor to use cutting-edge technologies to empower deaf primary school students in Sri Lanka. Three key elements make up the study: a sound recognition and classification system, an Android software for translating gestures in Sinhala Sign Language (SSL), and a mobile app for emotion recognition and text-tospeech in Sinhala. By promptly alerting caregivers to potential dangers, the sound recognition technology secures the security of deaf children at home, providing an invaluable layer of security. The Android software bridges the communication gap and improves family interactions by translating SSL gestures captured by the device's camera into textual representations. This promotes successful communication between deaf children and their parents. Convolutional Neural Networks (CNNs) are used in the mobile application to detect and understand emotions based on facial expressions. This enables non-verbal youngsters to communicate successfully through Sinhala textto-speech output with adaptive tone modulation. This research aims to build a caring and inclusive atmosphere, enabling increased independence and enhanced communication skills in deaf children by combining these advances. The suggested solutions could significantly improve the lives of deaf kids, providing them with opportunities for better learning, social interaction, and emotional health.
Background:Retinal vein occlusion(RVO)is one of the most common retinal vascular diseases leading to vision loss if not diagnosed and treated in *** diagnosis of central and branch RVO(CRVO and BRVO)can alleviate the ...
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Background:Retinal vein occlusion(RVO)is one of the most common retinal vascular diseases leading to vision loss if not diagnosed and treated in *** diagnosis of central and branch RVO(CRVO and BRVO)can alleviate the workload of ophthalmologists while facilitating early detection and treat-ment of RVO and laying the foundation for subsequent symptom grading,treatment planning,and ***,the development of a fast,high-performance,and robust diagnostic model is a crucial step toward achieving quantitative and accu-rate assessment of RVO *** there is an extensive research using fundus visual images for clinical assisted diagno-sis with deep learning models,there is a lack of focus on incor-porating doctors'text reports to further enhance the models.
Objectives:In this study,we propose a multi-modal medical visual-and-language learning model that utilizes fundus fluo-rescein angiography(FFA)images and physician analysis reports to classify BRVO and CRVO cases.
Methods:As shown in Fig.1,the proposed model utilizes an advanced convolutional neural network to extract visual features from FFA images for patient visual representation *** language representation learning,the model first extracts basic patient features such as gender,age,vision,and blood pressure,and then uses regular expression matching to obtain typical patient symptoms from expert text ***,we cre-ated a sign vocabulary for RVO patients,including exudate,macular edema,and intraretinal hemorrhage,among *** on this vocabulary,the proposed model analyzes patient symptom manifestations and learns symptom presentation(such as exudate stage and location).Finally,based on the patient's visual and text representation,the proposed model uses a fully connected(FC)layer for classification tasks.
Results:We evaluated the proposed model on a private dataset consisting of 101 patients and 1,265 FFA images,composed of 58 BRVO patients and 43 CRVO patie
At present, the safety monitoring of electric power sites mainly monitors the monitoring video through personnel, which has problems such as heavy workload, missed detection, and false alarms. In order to realize the ...
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Pseudo-Boolean optimization (PBO) is usually used to model combinatorial optimization problems, especially for some real-world applications. Despite its significant importance in both theory and applications, there ar...
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This research paper presents a comprehensive exploration of various components to enhance the capabilities of a digital assistant tailored for visually impaired individuals. The first component explores how various im...
This research paper presents a comprehensive exploration of various components to enhance the capabilities of a digital assistant tailored for visually impaired individuals. The first component explores how various image captioning architectures and Vision Encoder Decoder models can be used for better environmental interaction. The second component concerns with facial expression recognition for better social interaction and the third component is a currency note identification component that aims to aid visually impaired individuals with cash transaction whilst the final component that explores a voice bot aims to improve a voice bot and how to manage accents, speech accuracy and naturality using modern deep learning techniques. By investigating these components, this research advances assistive technology, empowering visually impaired individuals with a conversational digital assistant that enhances environmental interaction, supports social interactions, and aids in currency identification.
The Sunway family supercomputers have achieved a series of remarkable achievements. However, the toolchains provided by them are not perfect, which has brought great challenges to the development of high-performance a...
The Sunway family supercomputers have achieved a series of remarkable achievements. However, the toolchains provided by them are not perfect, which has brought great challenges to the development of high-performance application software. In this paper, a profiling and optimizing tool is proposed to assist people to analyze and optimize the performance of their programs. SWPFOPLD is independent of the application program and gathers the runtime performance data through the PMUs, an automatically hot functions rearrange optimization based on the performance data is furtherly accomplished. The evaluation shows that SWPFOPLD can be easily and effectively used to analyze and optimize the performance of the application programs.
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