AI-driven smart agriculture using hybrid transformer-CNN for real time disease detection in sustainable farming by Zhuo Zeng, Tariq Mahmood, Yu Wang, Amjad Rehman, Muhammad Akram Mujahid

“…This study introduces the AttCM-Alex model, a novel deep-learning framework designed to boost the detection and classification of plant diseases under challenging environmental conditions. …”
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geodl: An R package for geospatial deep learning semantic segmentation using torch and terra. by Aaron E Maxwell, Sarah Farhadpour, Srinjoy Das, Yalin Yang

“…Convolutional neural network (CNN)-based deep learning (DL) methods have transformed the analysis of geospatial, Earth observation, and geophysical data due to their ability to model spatial context information at multiple scales. …”
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Segmented Curve-Fitting Method for Continuum Removal in CRISM MTRDR data by P. Kumari, S. Soor, A. Shetty, S. G. Koolagudi

“…The identification score is improved by around 8% for the similarity matching method Weighted Sum of Spectrum Correlation and by around 1.5% for a Convolutional Neural Network. Furthermore, an SCF-based mineral identification framework demonstrates its effectiveness in identifying the dominant minerals on CRISM MTRDR hyperspectral data collected from different locations on the Martian surface.…”
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Design of Chinese traditional Jiaoyi (Folding chair) based on Kansei Engineering and CNN-GRU-attention by Xinyan Yang, Nan Zhang, Jiufang Lv, Jiufang Lv, Jiufang Lv

“…BackgroundsThis study innovatively enhances personalized emotional responses and user experience quality in traditional Chinese folding armchair (Jiaoyi chair) design through an interdisciplinary methodology.GoalTo systematically extract user emotional characteristics, we developed a hybrid research framework integrating web-behavior data mining.Methods1) the KJ method combined with semantic crawlers extracts emotional descriptors from multi-source social data; 2) expert evaluation and fuzzy comprehensive assessment reduce feature dimensionality; 3) random forest and K-prototype clustering identify three core emotional preference factors: “Flexible Refinement,” “Uncompromising Quality,” and “ergonomic stability.”DiscussionA CNN-GRU-Attention hybrid deep learning model was constructed, incorporating dynamic convolutional kernels and gated residual connections to address feature degradation in long-term semantic sequences. …”
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TDR-Model: Tomato Disease Recognition Based on Image Dehazing and Improved MobileNetV3 Model by Zhixiang Zhang, Tong Liu, Jinyu Gao, Meng Yang, Wenjun Luo, Fanqiang Lin

“…Additionally, we provide extensive ablation studies to evaluate effectiveness of the proposed framework.…”
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Medical Report Generation With Knowledge Distillation and Multi-Stage Hierarchical Attention in Vision Transformer Encoder and GPT-2 Decoder by Hilya Tsaniya, Chastine Fatichah, Nanik Suciati, Takashi Obi, Joong-Sun Lee

“…In this study, we propose a novel framework that integrates knowledge distillation and multi-stage hierarchical attention mechanisms to enhance the generation of comprehensive and accurate medical reports. …”
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Adaptive Outdoor Cleaning Robot with Real-Time Terrain Perception and Fuzzy Control by Raul Fernando Garcia Azcarate, Akhil Jayadeep, Aung Kyaw Zin, James Wei Shung Lee, M. A. Viraj J. Muthugala, Mohan Rajesh Elara

“…This paper proposes a terrain-aware cleaning framework that dynamically adjusts robot behavior based on real-time surface classification and slope estimation. …”
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Attention Feature Fusion Network via Knowledge Propagation for Automated Respiratory Sound Classification by Ida A. P. A. Crisdayanti, Sung Woo Nam, Seong Kwan Jung, Seong-Eun Kim

“…<italic>Methods:</italic> We developed a deep convolutional neural network (CNN) model that utilizes spectrographic representations of respiratory sounds within an image classification framework. …”
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Integrating non-linear radon transformation for diabetic retinopathy grading by Farida Mohsen, Samir Belhaouari, Zubair Shah

“…This study introduces RadFuse, a multi-representation deep learning framework that integrates non-linear RadEx-transformed sinogram images with traditional fundus images to enhance diabetic retinopathy detection and grading. …”
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A Non-Invasive Approach for Facial Action Unit Extraction and Its Application in Pain Detection by Mondher Bouazizi, Kevin Feghoul, Shengze Wang, Yue Yin, Tomoaki Ohtsuki

“…To address this, we present a quick, computationally efficient method for detecting action units (AUs) and their intensities—key indicators of health and emotion—using only 3D facial landmarks. Our proposed framework extracts 3D face landmarks from video recordings and employs a lightweight neural network (NN) to identify AUs and estimate AU intensities based on these landmarks. …”
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Multi-source remote sensing data for monitoring natural reserves: a case study on the Shaanxi Hanzhong crested ibis National Nature Reserve, China by Haoshan Wang, Yunwei Tang, Linhai Jing, Hui Li, Haifeng Ding, Changyong Dou

“…The paper proposes a framework to monitor human activities and evaluate habitat suitability for the Crested Ibis in the Shaanxi Hanzhong Nipponia nippon National Nature Reserve using multi-source satellite data. …”
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Unlocking transcranial FUS-EEG feature fusion for non-invasive sleep staging in next-gen clinical applications by Suneet Gupta, Praveen Gupta, Bechoo Lal, Aniruddha Deka, Hirakjyoti Sarma, Sheifali Gupta

“…Addressing the variations in electroencephalogram (EEG) and electrooculogram (EOG) signals across different sleep stages, this study introduces a transcranial focused ultrasound (tFUS) based multimodal feature fusion deep learning model (MFDL) for automated sleep staging. The proposed framework integrates two one-dimensional convolutional neural networks (1D-CNNs) to extract sleep-relevant features from EEG and EOG signals, followed by an adaptive feature fusion module that dynamically assigns weights based on feature significance. …”
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Graph-Based Radiomics Feature Extraction From 2D Retina Images by Ofelio Jorreia, Nuno Goncalves, Rui Cortesao

“…Within the radiomics framework, this study introduces a methodology to distinguish bifurcations from other structural variations in 2D local fragments of retinal vasculature. …”
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Enhancing Gamma Knife Cone-beam Computed Tomography Image Quality Using Pix2pix Generative Adversarial Networks: A Deep Learning Approach by Prabhakar Ramachandran, Darcie Anderson, Zachery Colbert, Daniel Arrington, Michael Huo, Mark B Pinkham, Matthew Foote, Andrew Fielding

“…Aims: The study aims to develop a modified Pix2Pix convolutional neural network framework to enhance the quality of cone-beam computed tomography (CBCT) images. …”
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Tree Species Classification at the Pixel Level Using Deep Learning and Multispectral Time Series in an Imbalanced Context by Florian Mouret, David Morin, Milena Planells, Cécile Vincent-Barbaroux

“…Validation on independent in situ data shows that all models struggle to predict in areas not well covered by training data, but even in this situation, the RF algorithm is largely outperformed by deep learning models for minority classes. The proposed framework can be easily implemented as a strong baseline, even with a limited amount of reference data.…”
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Human Scene Understanding Mechanism-Based Image Captioning for Blind Assistance by Jong-Hoon Kim, Sung-Wook Park, Jun-Ho Huh, Se-Hoon Jung, Chun-Bo Sim

“…In contrast to prior works that primarily rely on conventional convolutional architectures, the proposed model uniquely incorporates human-inspired visual perception principles and Vision Transformer-based global encoding, offering a novel and interpretable framework tailored for assistive image captioning.…”
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Learning Spectral&#x2013;Spatial-Former Deep Prior for Hyperspectral Image Superresolution by Zeinab Dehghan, Jingxiang Yang, Abdolraheem Khader, Jian Fang, Liang Xiao

“…This study presents a multistage optimization framework that leverages high- and low-frequency components, along with a quadratic splitting method, to address the SR problem. …”
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Attention-enhanced StrongSORT for robust vehicle tracking in complex environments by Wei Xu, Xiaodong Du, Ruochen Li, Bingjie Li, Yuhu Jiao, Lei Xing

“…To address these challenges, we propose AE-StrongSORT (Attention-Enhanced StrongSORT), an attention-enhanced tracking framework featuring three systematic innovations: first, the GAM-YOLO (global attention mechanism-YOLO)hybrid architecture integrates multi-scale feature fusion with a global attention mechanism (GC2f structure). …”
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Learnable Resized and Laplacian-Filtered U-Net: Better Road Marking Extraction and Classification on Sparse-Point-Cloud-Derived Imagery by Miguel Luis Rivera Lagahit, Xin Liu, Haoyi Xiu, Taehoon Kim, Kyoung-Sook Kim, Masashi Matsuoka

“…While cost effective, these sensors produce sparser point clouds, leading to poor feature representation and degraded performance in deep learning techniques, such as convolutional neural networks (CNN), for tasks like road marking extraction and classification, which are essential for HD map generation. …”
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Video Instance Segmentation Through Hierarchical Offset Compensation and Temporal Memory Update for UAV Aerial Images by Ying Huang, Yinhui Zhang, Zifen He, Yunnan Deng

“…On the self-built UAV-VIS dataset, our HT-VIS with PHOC surpasses the baseline SipMask by 2.1% and achieves the highest average segmentation accuracy of 37.4% in the CNN-based methods, demonstrating the effectiveness and robustness of our proposed framework.…”
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