Fast Identification and Detection Algorithm for Maneuverable Unmanned Aircraft Based on Multimodal Data Fusion by Tian Luan, Shixiong Zhou, Yicheng Zhang, Weijun Pan

“…This integrated solution provides cost-effective, high-precision drone surveillance for resource-constrained airports.…”
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Replay-Based Incremental Learning Framework for Gesture Recognition Overcoming the Time-Varying Characteristics of sEMG Signals by Xingguo Zhang, Tengfei Li, Maoxun Sun, Lei Zhang, Cheng Zhang, Yue Zhang

“…In addition, a comparison of full dataset training with incremental learning training demonstrates that the framework improves the recognition rate by nearly 1%, exhibits better recognition performance, significantly shortens the training time, reduces the cost of model updating and iteration, and is more suitable for practical applications. …”
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How to detect occluded crosswalks in overview images? Comparing three methods in a heavily occluded area by Yuanyuan Zhang, Joseph Luttrell, IV, Chaoyang Zhang

“…However, obtaining such data at a large scale is often challenging due to the high cost associated with traditional collection methods. …”
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4D trajectory lightweight prediction algorithm based on knowledge distillation technique by Weizhen Tang, Jie Dai, Zhousheng Huang, Boyang Hao, Weizheng Xie

“…The student network adopts a Temporal Convolutional Network–LSTM (TCN–LSTM) design, integrating dilated causal convolutions and two LSTM layers for efficient temporal modeling. …”
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Finger drawing on smartphone screens enables early Parkinson's disease detection through hybrid 1D-CNN and BiGRU deep learning architecture. by Zhaohui Zhu, E Wu, Pengfei Leng, Jiajun Sun, Mingming Ma, Zhigeng Pan

“…Our hybrid model combined multi-scale convolutional feature extraction (using parallel 1D-Convolutional branches) with bidirectional temporal pattern recognition (via gated recurrent unit [GRU] networks) to analyze movement abnormalities and detect the disease.…”
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Satellite-Based Validation of Contrail Prediction Models for Sustainable Aviation by Baddireddi Sree Chandana, Pelleti Nandieswar Reddy, Rithvika Alapati, Sai Aswath Reddy, Radha Doraisamy, Uma Sankari

“…The research offers a scalable and cost-effective solution for enhancing aviation sustainability and aligns with global efforts to combat climate change.…”
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Integrating Machine Learning and Multi-Objective Optimization in Biofuel Systems: A Review by Ivan P. Malashin, Dmitry A. Martysyuk, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…The optimization of biofuel production involves balancing multiple conflicting objectives such as yield maximization, cost minimization, and environmental impact reduction. …”
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ScarNet: Development and Validation of a Novel Deep CNN Model for Acne Scar Classification With a New Dataset by Masum Shah Junayed, Md Baharul Islam, Afsana Ahsan Jeny, Arezoo Sadeghzadeh, Topu Biswas, A. F. M. Shahen Shah

“…In this paper, a novel automated acne scar classification system is proposed based on a deep Convolutional Neural Network (CNN) model. First, a dataset of 250 images from five different classes is collected and labeled by four well-experienced dermatologists. …”
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Avnet: learning attitude and velocity for vehicular dead reckoning using smartphone by adapting an invariant EKF by Long Qian, Xinchuang Lin, Xiaoguang Niu, Qihai Huang, Leilei Li, Guangyi Guo, Zexin Wang, Ruizhi Chen

“…Abstract Smartphone-based vehicle navigation has become the primary choice in everyday life due to low cost and real-time traffic updates. However, for vehicle navigation applications in the Global Navigation Satellite System (GNSS)-denied scenario such as parking lot and tunnel, it is quite difficult to maintain robust and continuous positioning based on consumer-grade sensors. …”
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Energy saving by Artificial intelligence-based fault detection and diagnosis: 42 chiller case studies by Yen-Tang Chen, Da-Sheng Lee, Jhih-Jie Yang, Wei-Tao Huang, Yen-Po Liu

“…While previous studies have primarily focused on fault identification and maintenance cost reduction, empirical evidence regarding the energy-saving impact of AI-based FDD remains limited. …”
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Extensive Feature-Inferring Deep Network for Hyperspectral and Multispectral Image Fusion by Abdolraheem Khader, Jingxiang Yang, Sara Abdelwahab Ghorashi, Ali Ahmed, Zeinab Dehghan, Liang Xiao

“…The mathematical solutions class has serious challenges, e.g., computation cost, manually tuning parameters, and the absence of imaging models that laboriously affect the fusion process. …”
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Learning Spectral–Spatial-Former Deep Prior for Hyperspectral Image Superresolution by Zeinab Dehghan, Jingxiang Yang, Abdolraheem Khader, Jian Fang, Liang Xiao

“…To overcome this, we integrated our model into a deep convolutional neural network enhanced by a Transformer module for regularization. …”
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A Novel Federated Learning Framework for Sustainable and Efficient Breast Cancer Classification System (FL-L₂CNN-BCDet) by Nesma Abd El-Mawla, Mohamed A. Berbar, Nawal A. El-Fishawy, Mohamed A. El-Rashidy

“…To minimize communication cost and simultaneously achieve the best accuracy, the proposed FL framework develops a new DL architecture for mammography classification, taking into account the optimal number of rounds between client hosts and the central server. …”
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SIGNETS: Neural Network Architectures for m-QAM Soft Demodulation by Aravind R. Voggu, Kanish R, Nishith Akula, Lohitaksh Maruvada, Takanori Shimizu, Madhav Rao

“…We comparatively evaluate the members of the family of networks to find a Pareto-optimal Neural Network Demodulator with a balance of demodulation accuracy and computational cost, achieving an average accuracy of 99.658% across 4 dB to 24 dB SNR while requiring less than 16,000 Floating-Point Operations (FLOPs) for every demodulated QAM-16 symbol. …”
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EmotionNet-X: An Optimized CNN Architecture for Robust Facial Emotion Analysis by Syed Muhammad Aqleem Abbas, Qaisar Abbas, Syed Muhammad Naqi

“…Existing pretrained models suffer from high computational costs, limiting real-time IoT deployment. Deep Neural Networks (DNNs), particularly Convolutional Neural Networks (CNNs), are widely used for facial expression recognition (FER). …”
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MFCEN: A lightweight multi-scale feature cooperative enhancement network for single-image super-resolution by Jiange Liu, Yu Chen, Xin Dai, Li Cao, Qingwu Li

“…In recent years, significant progress has been made in single-image super-resolution with the advancements of deep convolutional neural networks (CNNs) and transformer-based architectures. …”
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Developing a multi-variate prediction model for COVID-19 from crowd-sourced respiratory voice data by Yuyang Yan, Wafaa Aljbawi, Sami O. Simons, Visara Urovi

“…Aim: COVID-19 has affected more than 223 countries worldwide and in the post-COVID era, there is a pressing need for non-invasive, low-cost, and highly scalable solutions to detect COVID-19. …”
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Computer Vision and Transfer Learning for Grading of Egyptian Cotton Fibres by Ahmed Rady, Oliver Fisher, Aly A. A. El-Banna, Haitham H. Emasih, Nicholas J. Watson

“…These results demonstrate the feasibility of developing a fast, low-cost, and low-skilled vision system that overcomes the inconsistencies and limitations of manual grading in the early stages of cotton fibre trading in Egypt.…”
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Evolving Hybrid Deep Neural Network Models for End-to-End Inventory Ordering Decisions by Thais de Castro Moraes, Jiancheng Qin, Xue-Ming Yuan, Ek Peng Chew

“…Notably, results showcase substantial benefits, yielding up to an 85% reduction in costs compared to a univariate benchmark and up to 40% savings compared to a feed-forward E2E deep learning architecture. …”
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Comparative Analysis of Machine Learning Algorithms for Antenna Alignments by Mohammad Al Bataineh, Dana I. Abu Abdoun, Mahmoud Al Ahmad

“…This is the first work to propose a data-driven antenna alignment method based solely on S-parameter analysis, offering a cost-effective and scalable alternative to complex imaging or optical systems. …”
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