A Line of Sight/Non Line of Sight Recognition Method Based on the Dynamic Multi-Level Optimization of Comprehensive Features by Ziyao Ma, Zhongliang Deng, Zidu Tian, Yingjian Zhang, Jizhou Wang, Jilong Guo

“…Experimental results show that the NLOS/LOS recognition method proposed in this paper has higher accuracy than other deep learning methods.…”
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Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography by Shiyi Cheng, Shuaibin Chang, Yunzhe Li, Anna Novoseltseva, Sunni Lin, Yicun Wu, Jiahui Zhu, Ann C. McKee, Douglas L. Rosene, Hui Wang, Irving J. Bigio, David A. Boas, Lei Tian

“…Here, we present a novel 3D imaging framework that combines S-OCT with a deep-learning digital staining (DS) model. This enhanced imaging modality integrates high-throughput 3D imaging, low sample variability and high interpretability, making it suitable for 3D histology studies. …”
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Design and Experimental Evaluation of a Smart Intra-Row Weed Control System for Open-Field Cabbage by Shenyu Zheng, Xueguan Zhao, Hao Fu, Haoran Tan, Changyuan Zhai, Liping Chen

“…The system integrates deep learning technology for accurate identification and localization of cabbage, enabling precise control and dynamic obstacle avoidance for the weeding knives. …”
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MaDis-Stereo: Enhanced Stereo Matching via Distilled Masked Image Modeling by Jihye Ahn, Hyesong Choi, Soomin Kim, Dongbo Min

“…In stereo matching, Convolutional Neural Networks (CNNs), a class of deep learning models designed to process grid-like data such as images, have traditionally served as the predominant architectures. …”
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Accelerating AI-Based Battery Management System’s SOC and SOH on FPGA by Satyashil D. Nagarale, B. P. Patil

“…This article presents an experimental study for the artificial intelligence (AI)-based data-driven prediction of lithium battery parameters SOC and SOH with the help of deep learning algorithms such as Long Short-Term Memory (LSTM) and bidirectional LSTM (BiLSTM). …”
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Prediction models for cognitive impairment in middle-aged patients with cerebral small vessel disease by Wei Zheng, Xiaoyan Qin, Ronghua Mu, Peng Yang, Bingqin Huang, Bingqin Huang, Zhixuan Song, Xiqi Zhu, Xiqi Zhu

“…PurposeThis study aims to develop hippocampal texture model for predicting cognitive impairment in middle-aged patients with cerebral small vessel disease (CSVD).MethodsThe dataset included 145 CSVD patients (Age, 52.662 ± 5.151) and 99 control subjects (Age, 52.576±4.885). An Unet-based deep learning neural network model was developed to automate the segmentation of the hippocampus. …”
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Habitat Distributions and Abundance of Four Wild Herbivores on the Qinghai–Tibetan Plateau: A Review by Tian Qiao, Chiwei Xiao, Zhiming Feng, Junzhi Ye

“…Furthermore, we critically compare three aspects of methods: transect surveys, machine learning (ML), and deep learning (DL) methods of studying WHs. The results show that since the 1990s, the distributions and abundance of WHs have exhibited a trend of initial decline followed by recovery, largely attributed to global climate warming and a decrease in illegal hunting. …”
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An optimized lightweight real-time detection network model for IoT embedded devices by Rongjun Chen, Peixian Wang, Binfan Lin, Leijun Wang, Xianxian Zeng, Xianglei Hu, Jun Yuan, Jiawen Li, Jinchang Ren, Huimin Zhao

“…YOLOv8, as an advanced deep learning model in the field of target detection, has attracted much attention for its excellent detection speed, high precision, and multi-task processing capability. …”
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Advances in colorectal cancer diagnosis using optimal deep feature fusion approach on biomedical images by Sultan Refa Alotaibi, Manal Abdullah Alohali, Mashael Maashi, Hamed Alqahtani, Moneerah Alotaibi, Ahmed Mahmud

“…Lately, computer-aided diagnosis (CAD) based on HI has progressed rapidly with the increase of machine learning (ML) and deep learning (DL) based models. This study introduces a novel Colorectal Cancer Diagnosis using the Optimal Deep Feature Fusion Approach on Biomedical Images (CCD-ODFFBI) method. …”
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A Novel Deep Hybrid Recommender System Based on Auto-encoder with Neural Collaborative Filtering by Yu Liu, Shuai Wang, M. Shahrukh Khan, Jieyu He

“…However, there is as yet no research combining collaborative filtering and content-based recommendation with deep learning. In this paper, we propose a novel deep hybrid recommender system framework based on auto-encoders (DHA-RS) by integrating user and item side information to construct a hybrid recommender system and enhance performance. …”
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Prediction of Future Terrorist Activities Using Deep Neural Networks by M. Irfan Uddin, Nazir Zada, Furqan Aziz, Yousaf Saeed, Asim Zeb, Syed Atif Ali Shah, Mahmoud Ahmad Al-Khasawneh, Marwan Mahmoud

“…Machine learning methods have been recently explored to develop techniques for counterterrorism based on artificial intelligence (AI). Since deep learning has recently gained more popularity in machine learning domain, in this paper, these techniques are explored to understand the behavior of terrorist activities. …”
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Mid-infrared spectra of dried and roasted cocoa (Theobroma cacao L.): A dataset for machine learning-based classification of cocoa varieties and prediction of theobromine and caffe... by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

“…This dataset provides a basis for further research, enabling the integration of mid-infrared spectral data with HPLC (as a standard) to fine-tune machine learning and deep learning models that could be used to simultaneously predict the theobromine and caffeine content, as well as cocoa variety in both dried and roasted cocoa samples using a non-destructive approach based on spectral data. …”
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A Novel Telerehabilitation System for Physical Exercise Monitoring in Elderly Healthcare by Muhammad Abrar Ashraf, Shaheryar Najam, Touseef Sadiq, Shabbab Algamdi, Hanan Aljuaid, Hameedur Rahman, Ahmad Jalal

“…These multimodal features are fused and input into a deep learning model for classification and correctness assessment. …”
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An Intelligent Crow Search Optimization and Bi-GRU for Forest Fire Detection System Using Internet of Things by Syed Abdul Moeed, Bellam Surendra Babu, M. Sreevani, B. V. Devendra Rao, R. Raja Kumar and Gouse Baig Mohammed

“…Crow Search Optimization (CSO) and fractional calculus are used to create an optimal solution in the proposed crow search fractional calculus optimization (CSFCO) algorithm for deep learning. CSO is inspired by the intelligent foraging behavior of crows, and when combined with fractional calculus, it provides a robust optimization framework that improves the accuracy and efficiency of the AI model. …”
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Profile to frontal face recognition in the wild using coupled conditional generative adversarial network by Fariborz Taherkhani, Veeru Talreja, Jeremy Dawson, Matthew C. Valenti, Nasser M. Nasrabadi

“…Abstract In recent years, with the advent of deep‐learning, face recognition (FR) has achieved exceptional success. …”
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SFDA-MEF: An Unsupervised Spacecraft Feature Deformable Alignment Network for Multi-Exposure Image Fusion by Qianwen Xiong, Xiaoyuan Ren, Huanyu Yin, Libing Jiang, Canyu Wang, Zhuang Wang

“…However, traditional methods and unsupervised deep-learning methods always exhibit inherent limitations in dealing with complex overlapping regions. …”
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Peripheral nerve injury induces dystonia-like movements and dysregulation in the energy metabolism: A multi-omics descriptive study in Thap1+/− mice by Colette Reinhold, Susanne Knorr, Rhonda L. McFleder, Lisa Harder-Rauschenberger, Tom Gräfenhan, Andreas Schlosser, Michael Sendtner, Jens Volkmann, Chi Wang Ip

“…Phenotypic analysis using an unbiased deep learning algorithm revealed that nerve-injured Thap1+/− mice exhibited significantly more dystonia like movements (DLM) over the course of the 12-week experiment compared to naive Thap1+/− mice. …”
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SVFRH: A Growth Stage-Based Compartmental Model for Predicting the Disease Incident in Tomato (Solanum lycopersicum) by Athira P. Shaji, S. Hemalatha

“…Over decades, research has primarily focused on addressing these challenges through computer vision and deep learning techniques. In this work, we employ a comprehensive modelling approach that combines compartmental and logistic regression models to thoroughly address disease dynamics in tomato crops, with a particular focus on tomato early blight diseases. …”
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A Dual-Stage Processing Architecture for Unmanned Aerial Vehicle Object Detection and Tracking Using Lightweight Onboard and Ground Server Computations by Odysseas Ntousis, Evangelos Makris, Panayiotis Tsanakas, Christos Pavlatos

“…The UAV transmits selected frames to the ground server, which handles advanced tracking, trajectory prediction, and target repositioning using state-of-the-art deep learning models. Communication between the UAV and the server is maintained through a high-speed Wi-Fi link, with a fallback to a 4G connection when needed. …”
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Decoding Gestures in Electromyography: Spatiotemporal Graph Neural Networks for Generalizable and Interpretable Classification by Hunmin Lee, Ming Jiang, Jinhui Yang, Zhi Yang, Qi Zhao

“…In recent years, significant strides in deep learning have propelled the advancement of electromyography (EMG)-based upper-limb gesture recognition systems, yielding notable successes across a spectrum of domains, including rehabilitation, orthopedics, robotics, and human-computer interaction. …”
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