FAO PRESS RELEASE “NATIONAL INCEPTION WORKSHOP: LIFECYCLE MANAGEMENT OF PESTICIDES AND DISPOSAL OF POPS (PERSISTENT ORGANIC POLLUTANTS) PESTICIDES IN KYRGYZSTAN” by Article Editorial

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Enhancing Cervical Cancer Classification: Through a Hybrid Deep Learning Approach Integrating DenseNet201 and InceptionV3 by Abhiram Sharma, R. Parvathi

“…This paper proposes a hybrid deep learning model integrating DenseNet201 and InceptionV3 to address the challenges in achieving accurate and reliable cervical cancer classification. …”
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Influence of Genetics, Immunity and the Microbiome on the Prognosis of Inflammatory Bowel Disease (IBD Prognosis Study): the protocol for a Copenhagen IBD Inception Cohort Study by Johan Burisch, Lene Terslev, Mikkel Østergaard, Annette Bøjer Jensen, Frank Krieger Jensen, Flemming Bendtsen, Charlotte Wiell, Mohamed Attauabi, Klaus Theede, Viktoria Fana, Hartwig Roman Siebner, Henrik S Thomsen, Jakob M Møller, Simon Francis Thomsen, Gorm Roager Madsen, Anne Vibeke Wewer, Rune Wilkens, Johan Ilvemark, Nora Vladimirova, Sanja Bay Hansen, Yousef Jesper Wirenfeldt Nielsen, Helene Andrea Sinclair Ingels, Trine Boysen, Jacob T Bjerrum, Christian Jakobsen, Maria Dorn-Rasmussen, Sabine Jansson, Yiqiu Yao, Ewa Anna Burian, Frederik Trier Møller, Kristina Bertl, Andreas Stavropoulos, Jakob B Seidelin

“…We have initiated a Danish population-based inception cohort study aiming to investigate the underlying mechanisms for the heterogeneous course of IBD, including need for, and response to, treatment.Methods and analysis IBD Prognosis Study is a prospective, population-based inception cohort study of unselected, newly diagnosed adult, adolescent and paediatric patients with IBD within the uptake area of Hvidovre University Hospital and Herlev University Hospital, Denmark, which covers approximately 1 050 000 inhabitants (~20% of the Danish population). …”
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A novel arc detection and identification method in pantograph-catenary system based on deep learning by Yue Yan, Hu Liu, Linfeng Gan, Runtong Zhu

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AI-Driven Plant Health Assessment: A Comparative Analysis of Inception V3, ResNet-50 and ViT with SHAP for Accurate Disease Identification in Taro by Valeria Maeda-Gutiérrez, Juan José Oropeza-Valdez, Luis C. Reveles-Gómez, Cristian Padron-Manrique, Osbaldo Resendis-Antonio, Luis Octavio Solís-Sánchez, Hector A. Guerrero-Osuna, Carlos Alberto Olvera Olvera

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Employing the concept of stacking ensemble learning to generate deep dream images using multiple CNN variants by Lafta Alkhazraji, Ayad R. Abbas, Abeer S. Jamil, Zahraa Saddi Kadhim, Wissam Alkhazraji, Sabah Abdulazeez Jebur, Bassam Noori Shaker, Mohammed Abdallazez Mohammed, Mohanad A. Mohammed, Basim Mohammed Al-Araji, Abdulkareem Z. Mohmmed, Wasiq Khan, Bilal Khan, Abir Jaafar Hussain

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Persistently different patterns of patient’s global assessment of health in rheumatoid arthritis are associated with pain and impaired function more than with inflammation: an inception cohort study over 15 years by Sofia Ajeganova, Ingiäld Hafström, Valentina Bala, Björn Svensson

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Multiple sclerosis diagnosis with brain MRI retrieval: A deep learning approach by R.M. Haggag, Eman M. Ali, M.E. Khalifa, Mohamed Taha

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Penerapan Blok SE-NET Pada Deep Learning Inceptionv3 untuk Meningkatkan Deteksi Penyakit Mpox pada Manusia by M. Bakhara Alief Rachman, Aliyah Kurniasih, Andika Sundawijaya, Ahlijati Nuraminah

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Applying YOLOv6 as an ensemble federated learning framework to classify breast cancer pathology images by Chhaya Gupta, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

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Intelligent Psychology Teaching System Based on Adaptive Neural Network by Xiaojia Pang

“…Among them, the number of interactive learning elements inception modules used by the network models GoogLeNet, Inception-v2, Inception-v4, and Inception-ResNet-v2 are 9, 10, 14, and 20, respectively. …”
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Observations of the Growth and Decay of Stall Cells during Stall and Surge in an Axial Compressor by Adam R. Hickman, Scott C. Morris

“…This research investigated unsteady events such as stall inception, stall-cell development, and surge. Stall is characterized by a decrease in overall pressure rise and nonaxisymmetric throughflow. …”
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Automated classification of elongated styloid processes using deep learning models-an artificial intelligence diagnostics by Anuradha Ganesan, N. Gautham Kumar, Prabhu Manickam Natarajan, Jeevitha Gauthaman

“…This comparison indicates that EfficientNetB5 outperformed InceptionV3 across all key metrics.ConclusionIn conclusion, our study presents a deep learning-based approach utilizing EfficientNetB5 and InceptionV3 to accurately categorize elongated styloid processes into distinct types based on their morphological characteristics from digital panoramic radiographs. …”
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Визначення віку людини за фото на основі нейронних мереж by Євгеній Вербенко, Ольга Мацуга

“…Після навчання VGG-19 та ResNet-50 досягли значень MAE 2.7 та 3.5 відповідно, тоді як Inception-v4 мала значення MAE 3.87. AlexNet продемонстрував значне перенавчання. …”
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Non-Destructive Estimation of Paper Fiber Using Macro Images: A Comparative Evaluation of Network Architectures and Patch Sizes for Patch-Based Classification by Naoki Kamiya, Kosuke Ashino, Yasuhiro Sakai, Yexin Zhou, Yoichi Ohyanagi, Koji Shibazaki

“…Expanding on studies that implemented EfficientNet-B0, we explore the effectiveness of six other deep learning networks, including DenseNet-201, DarkNet-53, Inception-v3, Xception, Inception-ResNet-v2, and NASNet-Large, in conjunction with enlarged patch sizes. …”
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Perbandingan Arsitektur Convolutional Neural Network Pada Klasifikasi Pneumonia, COVID-19, Lung Opacity, dan Normal Menggunakan Citra Sinar-X Thoraks by Agung Wahyu Setiawan

“…Selain itu, dilakukan perbandingan kinerja sembilan arsitektur CNN, yaitu Inception-ResNet, DenseNet201, InceptionV3, ResNet50v1, ResNet101, ResNet152, ResNet50v2, ResNet101v2, dan ResNet152v2. …”
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Development of metastasis and survival prediction model of luminal and non-luminal breast cancer with weakly supervised learning based on pathomics by Hui Liu, Linlin Ying, Xing Song, Xueping Xiang, Shumei Wei

“…Result Our results show that the Inception_v3 model shows a particularly robust patch recognition ability for estrogen receptor (ER) recognition. …”
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Image-Based Arabic Sign Language Recognition System Using Transfer Deep Learning Models by Qanita Bani Baker, Nour Alqudah, Tibra Alsmadi, Rasha Awawdeh

“…These impressive performance measures highlight the distinct capabilities of InceptionV3 in recognizing Arabic characters and underscore its robustness against overfitting. …”
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Optimizing multi label student performance prediction with GNN-TINet: A contextual multidimensional deep learning framework. by Xiaoyi Zhang, Yakang Zhang, Angelina Lilac Chen, Manning Yu, Lihao Zhang

“…The GNN-TINet utilizes InceptionNet, transformer architectures, and graph neural networks (GNN) to improve precision in multi-label student performance forecasting. …”
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Optimizing Pretrained Convolutional Neural Networks for Tomato Leaf Disease Detection by Iftikhar Ahmad, Muhammad Hamid, Suhail Yousaf, Syed Tanveer Shah, Muhammad Ovais Ahmad

“…We consider four CNN architectures, namely, VGG-16, VGG-19, ResNet, and Inception V3, and use feature extraction and parameter-tuning to identify and classify tomato leaf diseases. …”
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