Turbulence-Resilient Object Classification in Remote Sensing Using a Single-Pixel Image-Free Approach by Yin Cheng, Yusen Liao, Jun Ke

“…In this work, we propose a novel image-free classification framework using single-pixel imaging (SPI), which directly classifies targets from 1D measurements without reconstructing the image. …”
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Estimation of Potato Growth Parameters Under Limited Field Data Availability by Integrating Few-Shot Learning and Multi-Task Learning by Sen Yang, Quan Feng, Faxu Guo, Wenwei Zhou

“…These results collectively demonstrated that the proposed FSLGP framework could achieve reliable estimation of crop growth parameters using only a very limited number of in-field samples (approximately 80 samples). …”
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Estimation of lower limb torque: a novel hybrid method based on continuous wavelet transform and deep learning approach by Shu Xu, Tao Wang, Zenghui Ding, Yu Wang, Tongsheng Wan, Dezhang Xu, Xianjun Yang, Ting Sun, Meng Li

“…In view of this, this study proposes a cost-effective and user-friendly approach that integrates inertial measurement units (IMUs) with a novel deep learning framework for real-time lower limb joint torque estimation. …”
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DDoS Attack Detection in SDN-Assisted Federated Learning Environment Based on Contrastive Learning by Minghong Fan, Jinghua Lan, Yiyi Zhou, Mengshuang Pan, Junrong Li, Daqiang Zhang

“…The framework features a two-layer classification structure. …”
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Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models by Rijvan Beg, R. K. Pateriya, Deepak Singh Tomar

“…In this context, we propose a comprehensive framework that applies machine learning methods to enhance evidence collection and malware activity analysis. …”
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GearFaultNet: Novel Network for Automatic and Early Detection of Gearbox Faults by Proma Dutta, Kanchon Kanti Podder, Md. Shaheenur Islam Sumon, Muhammad E. H. Chowdhury, Amith Khandakar, Nasser Al-Emadi, Moajjem Hossain Chowdhury, M. Murugappan, Mohamed Arselene Ayari, Sakib Mahmud, S. M. Muyeen

“…The overall accuracy achieved by this framework is 94.04%. This shallow network can also be applied to estimate other mechanical faults in different machinery.…”
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Design of an Iterative Method for Time Series Forecasting Using Temporal Attention and Hybrid Deep Learning Architectures by Yuvaraja Boddu, A. Manimaran

“…Addressing these challenges, this paper introduces the Temporal Graph Attention Model for Time Series Analysis (TGAMTSA), a novel deep learning framework designed to enhance prediction accuracy and model adaptability in complex time series contexts and scenarios. …”
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Leveraging Prior Knowledge in Semi-Supervised Learning for Precise Target Recognition by Guohao Xie, Zhe Chen, Yaan Li, Mingsong Chen, Feng Chen, Yuxin Zhang, Hongyan Jiang, Hongbing Qiu

“…This study proposes DART-MT, a semi-supervised framework that integrates a Dual Attention Parallel Residual Network Transformer with a mean teacher paradigm, enhanced by domain-specific prior knowledge. …”
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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Xueyan Ji, Shamsulariffin Bin Samsudin, Muhammad Zarif Bin Hassan, Noor Hamzani Farizan, Yubin Yuan, Wang Chen

“…This study intends to develop a Spatial Temporal-Graph Convolutional Network (ST-GCN) action detection algorithm based on the MediaPipe framework. …”
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DeepAir: deep learning and satellite imagery to estimate high-resolution PM2.5 at scale by Wenxuan Guo, Zhaoping Hu, Ling Jin, Yanyan Xu, Marta C Gonzalez

“…DeepAir integrates a pre-trained convolutional neural network with the LightGBM method. …”
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Transferring Learned ECG Representations for Deep Neural Network Classification of Atrial Fibrillation with Photoplethysmography by Jayroop Ramesh, Zahra Solatidehkordi, Raafat Aburukba, Assim Sagahyroon, Fadi Aloul

“…In this work, we present a deep learning framework that leverages convolutional layers with a bidirectional long short-term memory (CNN-BiLSTM) network and an attention mechanism for effectively classifying raw AF rhythms from normal sinus rhythms (NSR). …”
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Maize and soybean yield prediction using machine learning methods: a systematic literature review by Ramandeep Kumar Sharma, Jasleen Kaur, Gary Feng, Yanbo Huang, Chandan Kumar, Yi Wang, Sandhir Sharma, Johnie Jenkins, Jagmandeep Dhillon

“…Numerous ML models are used, yet systemized framework guiding the crop-targeted selection of models, features, accuracy measures, and addressing associated challenges is lacking, specifically for soybean and maize, world’s vital crops. …”
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Enhancing security in 6G-enabled wireless sensor networks for smart cities: a multi-deep learning intrusion detection approach by Waqar Khan, Muhammad Usama, Muhammad Shahbaz Khan, Oumaima Saidani, Hussam Al Hamadi, Noha Alnazzawi, Mohammed S. Alshehri, Jawad Ahmad

“…As these networks evolve under 6G connectivity frameworks, their increasing reliance on heterogeneous communication protocols and decentralized architectures exposes them to sophisticated cyber threats. …”
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An Efficient Model for Real-Time Traffic Density Analysis and Management Using Visual Graph Networks by Nikhil Nigam, Dhirendra Pratap Singh, Jaytrilok Choudhary, Surendra Solanki

“…The proposed RDAMVGN framework incorporates both a LACF-YOLO detection model and a Faster Region-Based Convolutional Neural Network (Faster RCNN) detection model for high-speed and high-accuracy vehicle identification. …”
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A Combined Deep Learning Method with Attention-Based LSTM Model for Short-Term Traffic Speed Forecasting by Pan Wu, Zilin Huang, Yuzhuang Pian, Lunhui Xu, Jinlong Li, Kaixun Chen

“…Therefore, we propose a framework for short-term traffic speed prediction, including data preprocessing module and short-term traffic prediction module. …”
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High-precision segmentation and quantification of tunnel lining crack using an improved DeepLabV3+ by Zhutian Pan, Xuepeng Zhang, Yujing Jiang, Bo Li, Naser Golsanami, Hang Su, Yue Cai

“…EDeepLab improves upon the original DeepLabV3+ framework by replacing its backbone network with an optimized lightweight EfficientNetV2. …”
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MFA-net: Object detection for complex X-ray cargo and baggage security imagery. by Thanaporn Viriyasaranon, Seung-Hoon Chae, Jang-Hwan Choi

“…To our knowledge, the existing frameworks were developed to recognize threats using only baggage security X-ray scans. …”
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Deep-learning based multi-modal models for brain age, cognition and amyloid pathology prediction by Chenxi Wang, Weiwei Zhang, Ming Ni, Qiong Wang, Chang Liu, Linbin Dai, Mengguo Zhang, Yong Shen, Feng Gao

“…We designed a multi-modal deep-learning framework that employs 3D convolutional neural networks to analyze MRI and additional neural networks to evaluate demographic data. …”
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TLEABLCNN: Brain and Alzheimer’s Disease Detection Using Attention-Based Explainable Deep Learning and SMOTE Using Imbalanced Brain MRI by Erol Kina

“…This work presents a lightweight convolutional architecture based on EfficientNet with a Squeeze Attention Block using transfer learning. …”
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EmoBERTa–CNN: Hybrid Deep Learning Approach Capturing Global Semantics and Local Features for Enhanced Emotion Recognition in Conversational Settings by Mingfeng Zhang, Aihe Yu, Xuanyu Sheng, Jisun Park, Jongtae Rhee, Kyungeun Cho

“…To overcome these challenges, we developed EmoBERTa–CNN, a hybrid framework that combines EmoBERTa’s ability to capture global semantics with the capability of convolutional neural networks (CNNs) to extract local emotional features. …”
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