ENHANCED POLSAR IMAGE CLASSIFICATION USING DEEP CONVOLUTIONAL AND TEMPORAL CONVOLUTIONAL NETWORKS by Batool Anwar, Mohamed M. Morsey, Islam Hegazy, Zaki T. Fayed, Taha El-Arif

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Edge-guided slicing and inference (EGSI) with feature aggregation network for quantification of large defective temporary construction materials by Njoroge James Mugo, Akbar Ali, Song Jinwoo, Soonwook Kwon

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<italic>DynaTrack</italic>: Low-Power Channel-Aware Dynamic Smartphone Tracking Using UWB DL-TDOA by Junyoung Choi, Sagnik Bhattacharya, Joohyun Lee

“…It comprises a NLOS probability predictor based on a convolutional neural network (CNN), a dynamic ranging frequency control module, and an IMU sensor-based ranging filter. …”
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Time-domain brain: temporal mechanisms for brain functions using time-delay nets, holographic processes, radio communications, and emergent oscillatory sequences by Janet M. Baker, Peter Cariani

“…., sensation, cognition, motivation, attention, memory, learning, and motor action) is proposed that uses temporal codes, time-domain neural networks, correlation-based binding processes and signal dynamics. …”
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Predicting and Mitigating Delays in Cross-Dock Operations: A Data-Driven Approach by Amna Altaf, Adeel Mehmood, Adnen El Amraoui, François Delmotte, Christophe Lecoutre

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An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model by G. Abirami, S. Nagadevi, J. D. Dorathi Jayaseeli, T. Prabhakara Rao, R S M Lakshmi Patibandla, Rajanikanth Aluvalu, K Srihari

“…Investigators utilize DL models to identify possible objects inside an image. Convolutional neural network (CNN) is the major technique of DL, which enhances the learning qualities. …”
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Identification of Earthquake Precursors Origin and AI Framework for Automatic Classification for One of These Precursors by Ghada Ali, Lotfy Samy, Omar M. Saad, Ali G. Hafez, El-Sayed Hasaneen, Kamal AbdElrahman, Ibrahim Salah, Mohammed S. Fnais, Hamed Nofel, Ahmed M. Mohamed

“…The current study also introduces this automatic classification by developing various machine learning (ML) and Convolutional Neural Network (CNN) models to highlight the features characterizing each pattern. …”
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Infilling of missing rainfall radar data with a memory-assisted deep learning approach by J. Meuer, L. M. Bouwer, L. M. Bouwer, F. Kaspar, R. Lehmann, W. Karl, T. Ludwig, C. Kadow

“…We propose a deep convolutional neural network enhanced with a memory component to better account for temporal changes in precipitation fields. …”
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