UAV Hyperspectral Remote Sensing Image Classification: A Systematic Review by Zhen Zhang, Lehao Huang, Qingwang Wang, Linhuan Jiang, Yemao Qi, Shunyuan Wang, Tao Shen, Bo-Hui Tang, Yanfeng Gu

“…This article provides an in-depth and systematic review of UAV HSI classification techniques, systematically examining the evolution from traditional machine learning approaches, such as sparse coding, compressed sensing, and kernel methods, to cutting-edge deep learning frameworks, including convolutional neural networks, Transformer models, recurrent neural networks, graph convolutional networks, generative adversarial networks, and hybrid models. …”
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Deep learning with data transformation improves cancer risk prediction in oral precancerous conditions by John Adeoye, Yuxiong Su

“…Conclusion: Tabular-to-2D image data transformation may improve the use of structured input features for developing optimal intelligent models for oral cancer risk prediction in OL and OLD using convolutional networks. This approach may have the potential to robustly handle structured data in multimodal DL frameworks for oncological outcome prediction.…”
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Computer-vision based automatic rider helmet violation detection and vehicle identification in Indian smart city scenarios using NVIDIA TAO toolkit and YOLOv8 by Uttam U. Deshpande, Goh Kah Ong Michael, Sufola Das Chagas Silva Araujo, Vaidehi Deshpande, Rudragoud Patil, Ramchandra Alias Ameet Chate, Varun R. Tandur, Supreet S. Goudar, Shreya Ingale, Vaishnavi Charantimath

“…In the first stage, we utilized a highly efficient, robust, and accurate object identification DetectNet (Model 1) framework developed by NVIDIA, and it uses the ResNet18 Convolutional Neural Network (CNN) architecture as part of the Transfer Learning Toolkit known as TAO (Train, Adapt, Optimize). …”
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Building a machine learning-assisted echocardiography prediction tool for children at risk for cancer therapy-related cardiomyopathy by Lindsay A. Edwards, Christina Yang, Surbhi Sharma, Zih-Hua Chen, Lahari Gorantla, Sanika A. Joshi, Nicolas J. Longhi, Nahom Worku, Jamie S. Yang, Brandy Martinez Di Pietro, Saro Armenian, Aarti Bhat, William Border, Sujatha Buddhe, Nancy Blythe, Kayla Stratton, Kasey J. Leger, Wendy M. Leisenring, Lillian R. Meacham, Paul C. Nathan, Shanti Narasimhan, Ritu Sachdeva, Karim Sadak, Eric J. Chow, Patrick M. Boyle

“…We used holdout subsets in a 10-fold cross-validation framework and standard metrics to assess model performance (e.g., F1-score, area under the precision-recall curve [AUPRC]). …”
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Category semantic and global relation distillation for object detection by Yanpeng LIANG, Zhonggui MA, Zongjie WANG, Zhuo LI

“…To settle these questions, this study proposes a novel attention-based knowledge distillation framework for object detection, striking a better balance between efficiency and accuracy. …”
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Driver Drowsiness Detection Using Swin Transformer and Diffusion Models for Robust Image Denoising by Samy Abd El-Nabi, Ahmed F. Ibrahim, El-Sayed M. El-Rabaie, Osama F. Hassan, Naglaa F. Soliman, Khalil F. Ramadan, Walid El-Shafai

“…This study presents a robust and scalable driver drowsiness detection framework that integrates a Swin Transformer-based deep learning model with a diffusion model for image denoising. …”
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AI-driven pharmacovigilance: Enhancing adverse drug reaction detection with deep learning and NLP by Dr. Bharti Khemani, Dr. Sachin Malave, Samyukta Shinde, Mandvi Shukla, Razzaq Shikalgar, Harshita Talwar

“…This study proposes a hybrid AI-driven framework that integrates structured (e.g., patient demographics, lab results) and unstructured data (e.g., clinical notes) to detect ADRs using advanced deep learning and NLP methods. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…To the best of our knowledge, this is the first study to successfully combine EVT and machine learning for short- and long-term wind speed forecasting, providing a novel framework for reliable wind energy planning.…”
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Real-time detection of Chinese cabbage seedlings in the field based on YOLO11-CGB by Hang Shi, Hang Shi, Changxi Liu, Changxi Liu, Miao Wu, Miao Wu, Hui Zhang, Hui Zhang, Hang Song, Hang Song, Hao Sun, Hao Sun, Yufei Li, Yufei Li, Jun Hu, Jun Hu

“…However, the similarity between the characteristics of Chinese cabbage seedlings and some weeds is a great challenge for accurate detection.MethodsThis study introduces an enhanced detection method for Chinese cabbage seedlings, employing a modified version of YOLO11n, termed YOLO11-CGB. The YOLO11n framework has been augmented by integrating a Convolutional Attention Module (CBAM) into its backbone network. …”
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Intrusion Detection System to Advance Internet of Things Infrastructure-Based Deep Learning Algorithms by Hasan Alkahtani, Theyazn H. H. Aldhyani

“…An IoTID20 dataset attack was employed to develop the proposed system; it is a newly generated dataset from the IoT infrastructure. In this framework, three advanced deep learning algorithms were applied to classify the intrusion: a convolution neural network (CNN), a long short-term memory (LSTM), and a hybrid convolution neural network with the long short-term memory (CNN-LSTM) model. …”
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Deep Learning Approaches for Retinal Disease Diagnosis: Insights from Fundus and OCT Analysis by Kumar Sarvesh, Dixit Vipul, Gupta Madhuri

“…We investigate state-of-the-art architectures, including Vision Transformers (ViT), Convolutional Neural Networks (CNN), and hybrid frameworks on various datasets, including OCT2017, EyePACS, ACRIMA, and others. …”
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Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization by Dawen Wu, Yanfei Li, Zeyi Yang, Teng Yin, Xiaohang Chen, Jingyu Liu, Wenyi Shang, Bin Xie, Guoyuan Yang, Haixian Zhang, Longqian Liu

“…The preprocessing algorithm, based on a rotating bounding box detection framework, was trained and evaluated using precision, recall, and mean average precision (mAP) at various intersections over union thresholds. …”
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Evaluating CNN Architectures for the Automated Detection and Grading of Modic Changes in MRI: A Comparative Study by Li‐peng Xing, Gang Liu, Hao‐chen Zhang, Lei Wang, Shan Zhu, Man Du La Hua Bao, Yan‐ni Wang, Chao Chen, Zhi Wang, Xin‐yu Liu, Shuai Zhang, Qiang Yang

“…This study developed and investigated the performance of convolutional neural network (CNN) in detecting and grading MCs based on their maximum vertical extent. …”
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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…This framework aims to achieve three essential objectives: vehicle target detection, extraction of drivable road areas, and segmentation of lane lines. …”
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A Hybrid Deep Learning–Based Approach for Visual Field Test Forecasting by Ashkan Abbasi, PhD, Sowjanya Gowrisankaran, PhD, Wei-Chun Lin, MD, PhD, Xubo Song, PhD, Bhavna Josephine Antony, PhD, Gadi Wollstein, MD, Joel S. Schuman, MD, Hiroshi Ishikawa, MD

“…This study introduces a hybrid deep learning framework to enhance flexibility and accuracy in VF test forecasting. …”
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Advanced Hydro-Informatic Modeling Through Feedforward Neural Network, Federated Learning, and Explainable AI for Enhancing Flood Prediction by Shahariar Hossain Mahir, Md Tanjum An Tashrif, Md Ahsan Karim, Dipanjali Kundu, Anichur Rahman, Md. Amir Hamza, Fahmid Al Farid, Abu Saleh Musa Miah, Sarina Mansor

“…To address this, our research adopts the Federated Learning (FL) framework in an effort to train state-of-the-art deep learning models like Long Short-Term Memory Recurrent Neural Network (LSTM-RNN), Feed-Forward Neural Network (FNN) and Temporal Fusion Transformer-Convolutional Neural Network (TFT -CNN) on a 78-year dataset of rainfall, river flow, and meteorological variables from Sylhet and its upstream regions in Meghalaya and Assam, India. …”
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CrossModalSync: joint temporal-spatial fusion for semantic scene segmentation in large-scale scenes by Shuyi Tan, Yi Zhang, Yan Li, Byeong-Seok Shin

“…To address these, this paper introduces a new framework that balances accuracy and computational efficiency by utilizing temporal alignment (TA), projection multi-scale convolution (PMC), and priority point retention (PPR). …”
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Artificial intelligence in acupuncture: bridging traditional knowledge and precision integrative medicine by Guo-Liang Hou, Bao-Qiang Dong, Ben-Xing Yu, Jian-Yu Dai, Xing-Xing Lin, Ze-Zhong Cheng

“…We analyze key methodological innovations and challenges, and recommend future directions including the construction of federated multimodal data platforms, development of explainable AI frameworks, and promotion of open science practices. …”
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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…In the spatial domain, the Temporal Convolutional Network (TCN) models long-range dependencies by expanding causal convolutions, thereby capturing local and global spatial relationships. …”
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Video Coding Based on Ladder Subband Recovery and ResGroup Module by Libo Wei, Aolin Zhang, Lei Liu, Jun Wang, Shuai Wang

“…To address this issue, this paper proposes an innovative LadderConv framework, which combines discrete wavelet transform (DWT) with spatial and channel attention mechanisms. …”
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