Development of Ai-Based Crop Quality Grading Systems using Image Recognition by Dusi Prerna, Sharma Pooja

“…It also integrate Convolutional Neural Networks (CNN), Transfer Learning, Support Vector Machines (SVM) and Random Forest algorithms to label crop images into pre defined categories. …”
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Combining OBIA, CNN, and UAV imagery for automated detection and mapping of individual olive trees by Oumaima Ameslek, Hafida Zahir, Hanane Latifi, El Mostafa Bachaoui

“…With the development of technology, this process can be made more automated by using intelligent algorithms such as CNN.This work presents an OBIA-CNN (Object Based Image Analysis-Convolution Neural Network) approach that combines CNNs with OBIA to automatically detect and count olive trees from Phantom4 advanced drone imagery. …”
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AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view by Mostafa Jalilifar, Mahdi Sadeghi, Alireza Emami-Ardekani, Ahmad Bitarafan-Rajabi, Kouhyar Geravand, Parham Geramifar

“…Forty patients with thyroid cancers post-thyroidectomy surgery and 30 with neuroendocrine tumors underwent planar and SPECT/CT imaging. …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

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Machine learning-based multimodal data fusion for the Swiss land use statistics by Adrian Meyer, Gillian Milani, Natalie Lack, Maria Schönholzer, Denis Jordan

“…Aerial RGB and FCIR image-based Convolutional Neural Network (CNN) probability outputs are fused with multispectral Landsat-derived time series indices, digital elevation data, vegetation canopy models and cadastral information using a Random Forest (RF) post-classification step. …”
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Evaluation Model Based on the SGCNiFormer for the Influence of Different Storage Environments on Wheat Quality by Qingchuan Zhang, Zexi Song, Mingwen Bi

“…Wheat is a vital staple food crop, and its post-harvest storage is paramount to maintaining its quality. …”
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Development and Practice of Cloud Collaborative Platform for Downhole Measurement Tools by Che Yang, Yuan Guangjie, Qian Hongyu, Du Weiqiang, Wang Chenlong, Ding Jiping

“…Moreover， to solve the problem of low far-field ranging accuracy， multiple magnetic steering data mining algorithms such as support vector machine （SVM）， decision tree （DT）， multilayer perceptron （MLP） and convolutional neural network （CNN） were built and compared， indicating that the robustness and generalization of the multilayer perceptron algorithm is the best. …”
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Construction and Recording Method of a Three-Dimensional Model to Automatically Manage Thermal Abnormalities in Building Exteriors by Jonghyeon Yoon, Sangjun Hwang, Kyonghoon Kim, Sanghyo Lee

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Machine learning-enabled multiscale modeling platform for damage sensing digital twin in piezoelectric composite structures by Somnath Ghosh, Saikat Dan, Preetam Tarafder

“…The PUCCDM model-simulated macroscopic electromechanical and damage fields, in conjunction with RAMPs, provide a comprehensive time-dependent dataset for a convolutional long-short-term memory (ConvLSTM) network to learn microstructure-dependent electrical and damage field correlations. …”
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Performance Analysis of Eye Movement Event Detection Neural Network Models with Different Feature Combinations by Birtukan Adamu Birawo, Pawel Kasprowski

“…In this study, a combination of two-dimensional convolutional neural networks (2D-CNN) and long short-term memory (LSTM) layers is proposed to simultaneously classify input data into fixations, saccades, post-saccadic oscillations (PSOs), and smooth pursuits (SPs). …”
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Lightweight Dual-Attention Network for Concrete Crack Segmentation by Min Feng, Juncai Xu

“…Structural health monitoring in resource-constrained environments demands crack segmentation models that match the accuracy of heavyweight convolutional networks while conforming to the power, memory, and latency limits of watt-level edge devices. …”
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Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells. by Owen M O'Connor, Mary J Dunlop

“…Existing architectures developed for cell tracking based on convolutional neural networks (CNNs) have tended to fall short in managing the spatial and global contextual dependencies that are crucial for tracking cells. …”
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Comparison between coronal FLASH and sagittal double echo steady state MRI in detecting longitudinal cartilage thickness change by fully automated segmentation – Data from the FNIH... by Felix Eckstein, Akshay S. Chaudhari, David J. Hunter, Wolfgang Wirth

“…Post-processing involved automated registration of CNN-based subchondral bone segmentation to reference areas. …”
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Optimal Res-UNET architecture with deep supervision for tumor segmentation by Rahman Maqsood, Fazeel Abid, Jawad Rasheed, Jawad Rasheed, Jawad Rasheed, Onur Osman, Shtwai Alsubai

“…The proposed network was evaluated using extensive ablation studies, examining the effects of encoder complexity, convolutional filter count, and strategic post-processing.ResultsThe proposed Res-UNET with deep supervision outperformed other variants, achieving an average Dice score of 0.9498 through five-fold cross-validation. …”
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LarynxFormer: a transformer-based framework for processing and segmenting laryngeal images by Rune Mæstad, Abdul Hanan, Haakon Kristian Kvidaland, Haakon Kristian Kvidaland, Hege Clemm, Hege Clemm, Reza Arghandeh

“…These models include both convolutional-based and transformer-based methods. We propose a new framework called LarynxFormer, consisting of a pre-processing pipeline, transformer-based segmentation, and post-processing of laryngeal images. …”
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The Evolution of Biometric Authentication: A Deep Dive Into Multi-Modal Facial Recognition: A Review Case Study by Mohamed Abdul-Al, George Kumi Kyeremeh, Rami Qahwaji, Nazar T. Ali, Raed A. Abd-Alhameed

“…The survey highlights novel contributions such as using Generative Adversarial Networks (GANs) to generate synthetic disguised faces, Convolutional Neural Networks (CNNs) for feature extractions, and Fuzzy Extractors to integrate biometric verification with cryptographic security. …”
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ECGConVT: A Hybrid CNN and Vision Transformer Model for Enhanced 12-Lead ECG Images Classification by Mudassar Khalid, Charnchai Pluempitiwiriyawej, Abdulkadhem A. Abdulkadhem, Imran Afzal, Tien Truong

“…We propose ECGConVT framework that combines Convolutional Neural Network (CNN) module for extracting local features, and Vision Transformer (ViT) module for capturing global features. …”
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Building Damage Detection Using Deep Learning Architecture with Satellite Images: The Case of the 6 February 2023 Kahramanmaraş Earthquake by Zeynep Aygün, Merve Kocaman, Salih Aydemir, Berkant Konakoğlu

“…As a preprocessing step, interpolation was applied, resulting in 2211 images with a size of 128x128. A Convolutional Neural Network [2] algorithm was created using TensorFlow, a Python library, via Google Colab. …”
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A nnU-Net-based automatic segmentation of FCD type II lesions in 3D FLAIR MRI images by Shubham Joshi, Millie Pant, Millie Pant, Arnav Malhotra, Kusum Deep, Vaclav Snasel

“…Deep learning, especially convolutional neural networks, has shown great potential in automating image classification and segmentation by learning and extracting features. …”
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Impact of large language models and vision deep learning models in predicting neoadjuvant rectal score for rectal cancer treated with neoadjuvant chemoradiation by Hyun Bin Kim, Hong Qi Tan, Wen Long Nei, Ying Cong Ryan Shea Tan, Yiyu Cai, Fuqiang Wang

“…For CT scans, two different approaches with convolutional neural network were utilized to tackle the 3D scan entirely or tackle it slice by slice. …”
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