Suchergebnisse - "IEEE transactions on emerging topics in computational intelligence"

Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks von Hou, Jen-Cheng, Wang, Syu-Siang, Lai, Ying-Hui, Tsao, Yu, Chang, Hsiu-Wen, Wang, Hsin-Min

“… Speech enhancement (SE) aims to reduce noise in speech signals. Most SE techniques focus only on addressing audio information. In this paper, inspired by …”
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A Survey on Neural Network Interpretability von Zhang, Yu, Tino, Peter, Leonardis, Ales, Tang, Ke

“… Along with the great success of deep neural networks, there is also growing concern about their black-box nature. The interpretability issue affects people's …”
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A Survey of Embodied AI: From Simulators to Research Tasks von Duan, Jiafei, Yu, Samson, Tan, Hui Li, Zhu, Hongyuan, Tan, Cheston

“… There has been an emerging paradigm shift from the era of "internet AI" to "embodied AI," where AI algorithms and agents no longer learn from datasets of …”
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TransAttUnet: Multi-Level Attention-Guided U-Net With Transformer for Medical Image Segmentation von Chen, Bingzhi, Liu, Yishu, Zhang, Zheng, Lu, Guangming, Kong, Adams Wai Kin

“… Accurate segmentation of organs or lesions from medical images is crucial for reliable diagnosis of diseases and organ morphometry. In recent years, …”
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A Deep Learning Approach to Network Intrusion Detection von Shone, Nathan, Ngoc, Tran Nguyen, Phai, Vu Dinh, Shi, Qi

“… Network intrusion detection systems (NIDSs) play a crucial role in defending computer networks. However, there are concerns regarding the feasibility and …”
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Knowledge-Based Reinforcement Learning and Estimation of Distribution Algorithm for Flexible Job Shop Scheduling Problem von Du, Yu, Li, Jun-qing, Chen, Xiao-long, Duan, Pei-yong, Pan, Quan-ke

“… Inthis study, a flexible job shop scheduling problem with time-of-use electricity price constraint is considered. The problem includes machine processing …”
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Deep Contrastive Representation Learning With Self-Distillation von Xiao, Zhiwen, Xing, Huanlai, Zhao, Bowen, Qu, Rong, Luo, Shouxi, Dai, Penglin, Li, Ke, Zhu, Zonghai

“… Recently, contrastive learning (CL) is a promising way of learning discriminative representations from time series data. In the representation hierarchy, …”
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Deep Reinforcement Learning Based Adaptive Operator Selection for Evolutionary Multi-Objective Optimization von Tian, Ye, Li, Xiaopeng, Ma, Haiping, Zhang, Xingyi, Tan, Kay Chen, Jin, Yaochu

“… Evolutionary algorithms (EAs) have become one of the most effective techniques for multi-objective optimization, where a number of variation operators have …”
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Insights on Transfer Optimization: Because Experience is the Best Teacher von Gupta, Abhishek, Ong, Yew-Soon, Feng, Liang

“… Traditional optimization solvers tend to start the search from scratch by assuming zero prior knowledge about the task at hand. Generally speaking, the …”
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Machine Unlearning: Solutions and Challenges von Xu, Jie, Wu, Zihan, Wang, Cong, Jia, Xiaohua

“… Machine learning models may inadvertently memorize sensitive, unauthorized, or malicious data, posing risks of privacy breaches, security vulnerabilities, and …”
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Multi-Objective Feature Selection With Missing Data in Classification von Xue, Yu, Tang, Yihang, Xu, Xin, Liang, Jiayu, Neri, Ferrante

“… Feature selection (FS) is an important research topic in machine learning. Usually, FS is modelled as a bi-objective optimization problem whose objectives are: …”
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Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges von Al-Quraan, Mohammad, Mohjazi, Lina, Bariah, Lina, Centeno, Anthony, Zoha, Ahmed, Arshad, Kamran, Assaleh, Khaled, Muhaidat, Sami, Debbah, Merouane, Muhammad, Muhammad

“… New technological advancements in wireless networks have enlarged the number of connected devices. The unprecedented surge of data volume in wireless systems …”
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Advancements in Deep Learning for B-Mode Ultrasound Segmentation: A Comprehensive Review von Ansari, Mohammed Yusuf, Changaai Mangalote, Iffa Afsa, Meher, Pramod Kumar, Aboumarzouk, Omar, Al-Ansari, Abdulla, Halabi, Osama, Dakua, Sarada Prasad

“… Ultrasound (US) is generally preferred because it is of low-cost, safe, and non-invasive. US image segmentation is crucial in image analysis. Recently, deep …”
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Deep Reinforcement Learning Based Optimization Algorithm for Permutation Flow-Shop Scheduling von Pan, Zixiao, Wang, Ling, Wang, Jingjing, Lu, Jiawen

“… As a new analogy paradigm of human learning process, reinforcement learning (RL) has become an emerging topic in computational intelligence (CI). The synergy …”
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An Adaptive Archive-Based Evolutionary Framework for Many-Task Optimization von Chen, Yongliang, Zhong, Jinghui, Feng, Liang, Zhang, Jun

“… Multi-task optimization is an emerging research topic in computational intelligence community. In this paper, we propose a novel evolutionary framework, …”
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Light Gated Recurrent Units for Speech Recognition von Ravanelli, Mirco, Brakel, Philemon, Omologo, Maurizio, Bengio, Yoshua

“… A field that has directly benefited from the recent advances in deep learning is automatic speech recognition (ASR). Despite the great achievements of the past …”
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DFUNet: Convolutional Neural Networks for Diabetic Foot Ulcer Classification von Goyal, Manu, Reeves, Neil D., Davison, Adrian K., Rajbhandari, Satyan, Spragg, Jennifer, Yap, Moi Hoon

“… Globally, in 2016, 1 out of 11 adults suffered from diabetes mellitus. Diabetic foot ulcers (DFU) are a major complication of this disease, which if not …”
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Transformer and Graph Convolution-Based Unsupervised Detection of Machine Anomalous Sound Under Domain Shifts von Yan, Jingke, Cheng, Yao, Wang, Qin, Liu, Lei, Zhang, Weihua, Jin, Bo

“… Thanks to the development of deep learning, machine abnormal sound detection (MASD) based on unsupervised learning has exhibited excellent performance …”
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An Emerging Fuzzy Feature Selection Method Using Composite Entropy-Based Uncertainty Measure and Data Distribution von Xu, Weihua, Yuan, Kehua, Li, Wentao, Ding, Weiping

“… Feature selection based on neighborhood rough set is a noteworthy step in dealing with numerical data. Information entropy, proven in many theoretical analysis …”
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Random Walks: A Review of Algorithms and Applications von Xia, Feng, Liu, Jiaying, Nie, Hansong, Fu, Yonghao, Wan, Liangtian, Kong, Xiangjie

“… A random walk is known as a random process which describes a path including a succession of random steps in the mathematical space. It has increasingly been …”
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