Eff-ReLU-Net: a deep learning framework for multiclass wound classification by Sifat Ullah, Ali Javed, Muteb Aljasem, Abdul Khader Jilani Saudagar

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A Mobile Image-Driven PM2.5 Estimation Framework Using Deep Learning Techniques by Anupam Kamble, Somrawee Aramkul, Paskorn Champrasert

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Survey of research on efficient secure inference for deep learning by HU Peng, SUN Lei, HU Cuiyun, GUO Song, WANG Jingwen, WANG Zhihong, YAO Jingyi

“…Secure inference in deep learning with homomorphic encryption and secure multi-party computation has brought substantial computational and communication overhead. …”
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Multimodal hate speech detection: a novel deep learning framework for multilingual text and images by Furqan Khan Saddozai, Sahar K. Badri, Daniyal Alghazzawi, Asad Khattak, Muhammad Zubair Asghar

“…This study presents a deep learning framework that integrates bidirectional long short-term memory (BiLSTM) and EfficientNetB1 to classify hate speech in Urdu-English tweets, leveraging both text and image modalities. …”
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FCA-YOLO: An Efficient Deep Learning Framework for Real-Time Monitoring of Stored-Grain Pests in Smart Warehouses by Hongyi Ge, Jing Wang, Tong Zhen, Zhihui Li, Yuhua Zhu, Quan Pan

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A Multi-Factor-Fusion Framework for Efficient Prediction of Pedestrian-Level Wind Environment Based on Deep Learning by Zhen-Zhong Hu, Yan-Tao Min, Shuo Leng, Sunwei Li, Jia-Rui Lin

“…This study proposes a novel Multi-Factor-Fusion (MFF) framework that leverages deep learning techniques. …”
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Deep deterministic policy gradient - model-agnostic meta-learning framework: Efficient adaptation in continuous control tasks by Ebrahim Hamid Sumiea, Said Jadid Abdulkadir, Hitham Seddig Alhussian, Safwan Mahmood Al-Selwi, Alawi Alqushaibi, Mohammed Gamal Ragab, Abdul Muiz Fayyaz

“…This manuscript presents Meta-DDPG-MAML, which combines the Deep Deterministic Policy Gradient (DDPG) methodology with Model-Agnostic Meta-Learning (MAML) to augment both adaptability and efficiency. …”
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PULSE: A modular framework for predictive energy efficiency in heterogeneous data centers by Daniel Flores-Martin, Felipe Lemus-Prieto, Juan A. Rico-Gallego

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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

“…Then, we use three deep learning techniques, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), to classify the attacks. …”
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Conv1D-GRU-Self Attention: An Efficient Deep Learning Framework for Detecting Intrusions in Wireless Sensor Networks by Kenan Honore Robacky Mbongo, Kanwal Ahmed, Orken Mamyrbayev, Guanghui Wang, Fang Zuo, Ainur Akhmediyarova, Nurzhan Mukazhanov, Assem Ayapbergenova

“…To address this, the objective of this research is to design and evaluate a deep learning-based Intrusion Detection System (IDS) that is both accurate and efficient for real-time threat detection in WSNs. …”
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Digital twin based deep learning framework for personalized thermal comfort prediction and energy efficient operation in smart buildings by Ahmad Almadhor, Nejib Ghazouani, Belgacem Bouallegue, Natalia Kryvinska, Shtwai Alsubai, Moez Krichen, Abdullah Al Hejaili, Gabriel Avelino Sampedro

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Knowledge-Based Deep Learning for Time-Efficient Inverse Dynamics by Shuhao Ma, Yu Cao, Ian D. Robertson, Chaoyang Shi, Jindong Liu, Zhi-Qiang Zhang

“…In this paper, we propose a knowledge-based deep learning framework for time-efficient inverse dynamic analysis, which can predict muscle activation and muscle forces from joint kinematic data directly while not requiring any label information during model training. …”
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FL-QNNs: Memory Efficient and Privacy Preserving Framework for Peripheral Blood Cell Classification by Meenakshi Aggarwal, Vikas Khullar, Nitin Goyal, Bhavani Sankar Panda, Hardik Doshi, Nafeesh Ahmad, Vivek Bhardwaj, Gaurav Sharma

“…This study proposes a resource efficient, privacy preserving, optimized memory framework by incorporating two approaches: Federated learning and quantized neural network (FL-QNNs) for peripheral blood cell (PBC) image classification. …”
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A novel lightweight deep learning framework using enhanced pelican optimization for efficient cyberattack detection in the Internet of Things environments by Yaozhi Chen, Yan Guo, Yun Gao, Baozhong Liu

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Adaptive Transit Signal Priority Control for Traffic Safety and Efficiency Optimization: A Multi-Objective Deep Reinforcement Learning Framework by Yuxuan Dong, Helai Huang, Gongquan Zhang, Jieling Jin

“…This study introduces a multi-objective deep reinforcement learning (DRL)-based adaptive transit signal priority control framework designed to enhance safety and efficiency in mixed-autonomy traffic environments. …”
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Smart Waste Management Framework for Green Cities: Integrating IoT, LoRa, and Deep Learning for Efficient Waste Classification and Management by Suprava Ranjan Laha, Khalid Al Smadi, Ahmad Khader Habboush, Binod Kumar Pattanayak, Saumendra Pattnaik, Bibhuprasad Mohanty

“…To overcome these difficulties, a smart waste management framework was proposed for environmentally friendly cities, combining the Internet of Things (IoT), long-range (LoRa) technology, and Deep Learning techniques. …”
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Ensemble deep learning and EfficientNet for accurate diagnosis of diabetic retinopathy by Lakshay Arora, Sunil K. Singh, Sudhakar Kumar, Hardik Gupta, Wadee Alhalabi, Varsha Arya, Shavi Bansal, Kwok Tai Chui, Brij B. Gupta

“…Addressing this challenge head-on, this study introduces an innovative deep learning framework tailored for DR diagnosis. …”
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Efficient and secure multi-party computation protocol supporting deep learning by Shancheng Zhang, Gang Qu, Zongyang Zhang, Minzhe Huang, Haochun Jin, Liqun Yang

“…Abstract Privacy-preserving deep learning based on secure multi-party computation (MPC) has emerged as a critical research focus in recent years. …”
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Interpretable Deep Learning for Efficient Code Smell Prioritization in Software Development by Maaeda M. Rashid, Mohd Hafeez Osman, Khaironi Yatim Sharif, Hazura Zulzalil

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Efficient sepsis detection using deep learning and residual convolutional networks by Ahmed S. Almasoud, Ghada Moh Samir Elhessewi, Munya A. Arasi, Abdulsamad Ebrahim Yahya, Menwa Alshammeri, Donia Badawood, Faisal Mohammed Nafie, Mohammed Assiri

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