MAL-Net: Model-Adaptive Learned Network for Slow-Time Ambiguity Function Shaping by Jun Wang, Xiangqing Xiao, Jinfeng Hu, Ziwei Zhao, Kai Zhong, Chaohai Li

“…Furthermore, we observe that the gradient descent model over the CCM can be unfolded as a Deep Learning (DL) network. Therefore, byeveraging the powerfulearning ability of DL and the CCM gradient descent model, we propose a Model-Adaptive Learned Network (MAL-Net) method without relaxation. …”
Get full text

Attention-Based CNN Fusion Model for Emotion Recognition During Walking Using Discrete Wavelet Transform on EEG and Inertial Signals by Yan Zhao, Ming Guo, Xiangyong Chen, Jianqiang Sun, Jianlong Qiu

“…Accurate recognition of emotion is achieved by training in an end-to-end deep learning fashion and taking into account multi-modal fusion. …”
Get full text

A Novel Long Short-Term Memory Predicted Algorithm for BDS Short-Term Satellite Clock Offsets by Tailai Wen, Gang Ou, Xiaomei Tang, Pengyu Zhang, Pengcheng Wang

“…To deal with this problem, we proposed a deep learning-based approach for BDS short-term satellite clock offset modeling which utilizes the superiority of Long Short-Term Memory (LSTM) derived from Recurrent Neural Networks (RNN) in time series modeling, and we call it QPLSTM. …”
Get full text

Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete by Fahid Aslam, Furqan Farooq, Muhammad Nasir Amin, Kaffayatullah Khan, Abdul Waheed, Arslan Akbar, Muhammad Faisal Javed, Rayed Alyousef, Hisham Alabdulijabbar

“…Moreover, variable intensity and correlation have shown that deep learning can be used to know the exact amount of materials in civil engineering rather than doing experimental work. …”
Get full text

CenterNet-Elite: A Small Object Detection Model for Driving Scenario by Lingling Wang, Xiang Li, Xiaoyan Chen, Bin Zhou

“…With the rapid development of deep learning networks, the accuracy of generic object detection has consistently improved. …”
Get full text

Artificial Intelligence-Based Skin Lesion Analysis and Skin Cancer Detection by Momina Qureshi, Muhammad Athar Javed Sethi, Sayed Shahid Hussain

“…In response, this study presents a groundbreaking approach that makes use of an ensemble of twelve pre-trained deep learning models, including InceptionV3, VGG16, VGG19, Xception, DensNet121, DensNet201, ResNet152V2, MobileNet, MobileNetV2, ConvNeXtLarge, NASNetMobile, and InceptionResNetV2. …”
Get full text

Fast 3D Transmission Tower Detection Based on Virtual Views by Liwei Zhou, Jiaying Tan, Jing Fu, Guiwei Shao

“…However, traditional 3D target detection techniques, which involve searching the entire 3D space, are marred by low accuracy and high computational demands. Although deep learning-based 3D target detection methods have significantly improved detection precision, they rely on a large volume of 3D target samples for training and are sensitive to point cloud data density. …”
Get full text

Masked Modeling-Based Ultrasound Image Classification via Self-Supervised Learning by Kele Xu, Kang You, Boqing Zhu, Ming Feng, Dawei Feng, Cheng Yang

“…Recently, deep learning-based methods have emerged as the preferred approach for ultrasound data analysis. …”
Get full text

Learning to Boost the Performance of Stable Nonlinear Systems by Luca Furieri, Clara Lucia Galimberti, Giancarlo Ferrari-Trecate

“…However, maintaining closed-loop stability while boosting the performance of nonlinear control systems using data-driven and deep-learning approaches stands as an important unsolved challenge. …”
Get full text

Deep empirical neural network for optical phase retrieval over a scattering medium by Huaisheng Tu, Haotian Liu, Tuqiang Pan, Wuping Xie, Zihao Ma, Fan Zhang, Pengbai Xu, Leiming Wu, Ou Xu, Yi Xu, Yuwen Qin

“…The DENN might shed new light on the applications of deep learning in physics, information science, biology, chemistry and beyond.…”
Get full text

Bilingual hate speech detection on social media: Amharic and Afaan Oromo by Teshome Mulugeta Ababu, Michael Melese Woldeyohannis, Emuye Bawoke Getaneh

“…In this work, a Bilingual hate speech detection for Amharic and Afaan Oromo languages were conducted using four different deep learning classifiers (CNN, BiLSTM, CNN-BiLSTM, and BiGRU) and three feature extraction (Keras word embedding, word2vec, and FastText) techniques. …”
Get full text

Eigen Solution of Neural Networks and Its Application in Prediction and Analysis of Controller Parameters of Grinding Robot in Complex Environments by Shixi Tang, Jinan Gu, Keming Tang, Wei Ding, Zhengyang Shang

“…Lastly, to verify the eigen solution theory of neural networks, the proposed theory was applied to a novel prediction and analysis model of controller parameters of grinding robot in complex environments with deep neural networks and then build prediction model with deep learning neural networks for controller parameters of grinding robot. …”
Get full text

A Real-Time Semantic Segmentation Method of Sheep Carcass Images Based on ICNet by Shida Zhao, Guangzhao Hao, Yichi Zhang, Shucai Wang

“…The characteristics of each part of the sheep carcass are connected to each other and have similar features, which make it difficult to identify and detect, but with the development of image semantic segmentation technology based on deep learning, it is possible to explore this technology for real-time recognition of the 3 parts of the sheep carcass. …”
Get full text

Developing a TinyML Image Classifier in an Hour by Riccardo Berta, Ali Dabbous, Luca Lazzaroni, Danilo Pietro Pau, Francesco Bellotti

“…The notebook implements a methodology involving hyperparameter tuning and comparison of different shallow and deep learning models, with quantization. It exports TensorFlow Lite models, deployable on several microcontroller families, and optionally exploits the STM32Cube.AI developer cloud service, which allows benchmarking the developed models on a set of real-world tiny hardware target platforms. …”
Get full text

Development of Risk Activity Detection System for Forklifts Based on Inertial Sensors by Luciano Radrigan, Sebastian E. Godoy

“…This article shows a cost-effective solution proposal to implement an inertial sensor network with a dedicated wireless communication and automatic deep-learning algorithms to detect forklift risk events. …”
Get full text

Accelerating spin Hall conductivity predictions via machine learning by Jinbin Zhao, Junwen Lai, Jiantao Wang, Yi‐Chi Zhang, Junlin Li, Xing‐Qiu Chen, Peitao Liu

“…Here, we have developed a residual crystal graph convolutional neural network (Res‐CGCNN) deep learning model to classify and predict SHCs solely based on the structural and compositional information. …”
Get full text

DR-Z2AN: dual-recurrent neural network with a tri-channel attention mechanism for financial management prediction by Salem Knifo, Ahmad Alzubi

“…Therefore, in order to resolve these limitations; a deep learning-based model is developed in this study for efficient financial management prediction. …”
Get full text

Classification of tomato leaf disease using Transductive Long Short-Term Memory with an attention mechanism by Aarthi Chelladurai, D.P. Manoj Kumar, S. S. Askar, Mohamed Abouhawwash, Mohamed Abouhawwash

“…Thus, numerous research studies have been introduced based on deep learning models for the efficient classification of tomato leaf disease. …”
Get full text

A hybrid CNN-LSTM model with adaptive instance normalization for one shot singing voice conversion by Assila Yousuf, David Solomon George

“…Traditional voice conversion techniques primarily emphasize singer similarity, often leading to robotic-sounding singing voices. Deep learning-based singing voice conversion techniques, however, focus on disentangling singer-dependent and singer-independent features. …”
Get full text

Multi-Sensor Information Fusion with Multi-Scale Adaptive Graph Convolutional Networks for Abnormal Vibration Diagnosis of Rolling Mill by Rongrong Peng, Changfen Gong, Shuai Zhao

“…However, most of the existing deep learning (DL) based methods exploit only single sensor information and Euclidean space data, which results in incomplete information contained in the features extracted by in-depth networks. …”
Get full text