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ACL-SAR: model agnostic adversarial contrastive learning for robust skeleton-based action recognition
Human skeleton data have been widely explored in action recognition and the human–computer interface recently, thanks to off-the-shelf motion sensors...
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Machine learning-driven performance assessment of network-on-chip architectures
System-on-chip designs for high-performance computing systems widely use network-on-chip (NoC) technology. The critical metrics such as latency,...
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On Stage-Wise Backpropagation for Improving Cheng’s Method for Fully Connected Cascade Networks
In this journal, Cheng has proposed a backpropagation ( BP ) procedure called BPFCC for deep fully connected cascaded ( FCC ) neural network learning in...
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Secure electronic monitoring of sex offenders
Electronic monitoring is a viable approach to controlling sex offenders and making the environment safe for victims. Two technologies are currently...
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Industrial product surface defect detection via the fast denoising diffusion implicit model
In the age of intelligent manufacturing, surface defect detection plays a pivotal role in the automated quality control of industrial products,...
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Certifying Accuracy, Privacy, and Robustness of ML-Based Malware Detection
Recent advances in artificial intelligence (AI) are radically changing how systems and applications are designed and developed. In this context, new...
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A review on emotion detection by using deep learning techniques
Along with the growth of Internet with its numerous potential applications and diverse fields, artificial intelligence (AI) and sentiment analysis...
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Car energy efficiency and emissions in the built environment
To mitigate climate change and safeguard energy security, it is necessary to limit car dependence, reduce car weights, and shift to alternative car...
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Addressing the traveling salesperson problem with frequency fitness assignment and hybrid algorithms
The traveling salesperson problem (TSP) is one of the most iconic hard optimization tasks. With frequency fitness assignment (FFA), a new approach to...
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An enhanced teaching–learning-based optimization for the flexible job shop scheduling problem considering worker behaviours
In actual workshop scheduling, processing time is influenced by worker behaviours, such as learning, forgetting, fatigue and recovery. However, in...
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A novel PLS technique for secure ESM based MIMO systems
Multiple-input multiple-output systems with spatial modulation has evolved into an energy efficient and less complex wireless transmission system due...
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An efficient approach of epilepsy seizure alert system using IoT and machine learning
Epilepsy is a neurological disorder that affects millions of people worldwide, and it is characterized by recurrent seizures that can vary in...
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Artificial Intelligence enabled cognitive computer-centered digital analysis model for examination of the children’s mental health
Mental health plays an important role for how a person act, think and feel. Specially in the case of students it’s become very crucial and they...
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Emergent cooperation from mutual acknowledgment exchange in multi-agent reinforcement learning
Peer incentivization (PI) is a recent approach where all agents learn to reward or penalize each other in a distributed fashion, which often leads to...
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Threshold ring signature: generic construction and logarithmic size instantiation
A ring signature is a variant of normal digital signature and protects the privacy of a specific signer in the sense that a ring signature can be...
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Ensemble machine learning for intelligent condition monitoring
Traditionally, the maintenance process in engineering has been a costly and time-consuming process that requires large amounts of resources and...
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Fuzzy nominal sets
In this paper, we use two approaches to define the concept of fuzzy nominal sets: classic and universal algebraic. We see that the fuzzy nominal sets...
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An artificial bee colony algorithm for the minimum edge-dilation K-center problem
This paper studies the minimum edge-dilation K -center (MEDKC) problem for edge-weighted, undirected and connected graphs. This problem which is
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A modified radiation model based on the characteristics of airline network under large-scale disruptions
The radiation model is widely used in traffic demand forecasting. However, when applying the radiation model in the aviation field, it overestimates...
