Suchergebnisse - Conventional autoen-coder

Unsupervised Convolutional Autoencoder-Based Feature Learning for Automatic Detection of Plant Diseases von Pardede, Hilman F., Suryawati, Endang, Sustika, Rika, Zilvan, Vicky

“… Developing an automatic detector of plant diseases is one of application fields in machine learning. Ground-truth diagnoses of plant diseases which are …”
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Application of a Convolutional Autoencoder to Half Space Radar Hrrp Recognition von Yu, Shi-Hao, Xie, Yong-Jun

“… Conventional deep models of representation learning used for HRRP target recognition commonly use the vanilla autoen-coder and deep belief net (DBN …”
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Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper) von Alam, Mahabubul, Kundu, Satwik, Topaloglu, Rasit Onur, Ghosh, Swaroop

“… Image classification is a major application domain for conventional deep learning (DL …”
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A Hybrid Deep Learning Approach for Detecting Anomalies in Real-Time Data Streams von Mishra, Aditya Mohan, Yadav, Daksh, Shakya, Ananmaya, Jayesh, Vagh, Bala, Er. Neetu

“… Conventional anomaly detection approaches, such machine learning models and statistical techniques, have trouble processing high-dimensional data, adjusting to concept drift, and sustaining low …”
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DFD-SS: Document Forgery Detection using Spectral – Spatial Features for Hyperspectral Images von Jaiswal, Garima, Sharma, Arun, Kumar Yadav, Sumit

“… , which is not possible by conventional imaging. Deep learning is an edge-cutting technology known for solving critical problems in various domains …”
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A Novel Hybrid Attentive Convolutional Autoencoder (HACA) Framework for Enhanced Epileptic Seizure Detection von Vaddi, Venkata Narayana, Sikha, Madhu Babu, Kodali, Prakash

“… This study presents a Hybrid Attentive Convolutional Autoen-coder (HACA) framework designed to address challenges in EEG signal processing for seizure detection …”
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Denoising Convolutional Variational Autoencoders-Based Feature Learning for Automatic Detection of Plant Diseases von Zilvan, Vicky, Ramdan, Ade, Suryawati, Endang, Kusumo, R. Budiarianto S., Krisnandi, Dikdik, Pardede, Hilman F.

“… However, conventional machine-learning techniques are limited in their ability to process raw data directly …”
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Feedback Convolution Based Autoencoder for Dimensionality Reduction in Hyperspectral Images von Pande, Shivam, Banerjee, Biplab

“… However, one of the main limitations of conventional CNNs is that they only have forward connections …”
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Generative neural network based spectrum sharing using linear sum assignment problems von Zaky, Ahmed B., Huang, Joshua Zhexue, Wu, Kaishun, ElHalawany, Basem M.

“… Spectrum management and resource allocation (RA) problems are challenging and critical in a vast number of research areas such as wireless communications and …”
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Deep-Learning-based Channel Estimation for Chaotic Wireless Communication von Yin, Hui-Ping, Zhao, Xiao-Hui, Yao, Jun-Ling, Ren, Hai-Peng

“… and significantly outperforms the conventional schemes in terms of the channel estimation MSE, as well as the BER …”
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APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models von Benabderrahmane, Sidahmed, Valtchev, Petko, Cheney, James, Rahwan, Talal

“… or conventional anomaly detection models, APT-LLM leverages LLMs to encode process-action provenance traces into semantically rich …”
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Bit-wise Autoencoder for Multiple Antenna Systems von Dorner, Sebastian, Rottacker, Sarah, Gauger, Marc, Brink, Stephan ten

“… We propose an end-to-end learned bit-wise autoen-coder neural network (NN) for open loop multiple-input multiple-output (MIMO …”
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Explainable Credit Scoring Through Generative Adversarial Networks von Han, Seongil

“… Credit scoring has been playing a vital role in mitigating financial risk that could affect the sustainability of financial institutions. An accurate and …”
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An Experimentally-Validated Coupled Opto-Thermal-Electrical Model for PV Performance and Reliability von Sun, Yubo

“… Photovoltaics (PV) are a renewable energy technology experiencing rapidly increasing commercial adoption today. Nonetheless, many proposed PV applications …”
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