End-to-end 3D instance segmentation of synthetic data and embryo microscopy images with a 3D Mask R-CNN by Gabriel David, Emmanuel Faure

“…The necessity of 3D approaches arises from the limitations of two-dimensional (2D) techniques when applied to 3D data due to the lack of global context. A critical task in medical and microscopy 3D image analysis is instance segmentation, which is inherently complex due to the need for accurately identifying and segmenting multiple object instances in an image. …”
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SDDGRNets: Level–Level Semantically Decomposed Dynamic Graph Reasoning Network for Remote Sensing Semantic Change Detection by Zhuli Xie, Gang Wan, Yunxia Yin, Guangde Sun, Dongdong Bu

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Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning by Christopher Kormpos, Fotios Zantalis, Stylianos Katsoulis, Grigorios Koulouras

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A New Bearing Fault Diagnosis Method Based on Deep Transfer Network and Supervised Joint Matching by Chengyao Liu, Fei Dong, Kunpeng Ge, Yuanyuan Tian

“…To overcome these problems, by integrating the superiority of deep learning method and feature-based transfer learning method, this work proposes an innovative cross-domain fault diagnosis framework based on deep transfer convolutional neural network and supervised joint matching. First, the continue wavelet transform is used to process original bearing vibration signals and extract time-frequency images. …”
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Development of a transdisciplinary education concept to prepare textile technology students for dealing with AI by Lennart Hellweg, Johanna Bulthaupt, Alen Tabakovic, Mathias Beer

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Development of a transdisciplinary education concept to prepare textile technology students for dealing with AI by Lennart Hellweg, Johanna Bulthaupt, Alen Tabakovic, Mathias Beer

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AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

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Partial image encryption using format-preserving encryption in image processing systems for Internet of things environment by Wonyoung Jang, Sun-Young Lee

“…Concomitant with advances in technology, the number of systems and devices that utilize image data has increased. Nowadays, image processing devices incorporated into systems, such as the Internet of things, drones, and closed-circuit television, can collect images of people and automatically share them with networks. …”
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De la base au réseau. L'apport des bases de données à l'étude des réseaux by Jean-Pierre Dedieu, Álvaro Chaparro

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Deep convolutional neural network architecture for facial emotion recognition by Dayananda Pruthviraja, Ujjwal Mohan Kumar, Sunil Parameswaran, Vemulapalli Guna Chowdary, Varun Bharadwaj

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Application of the extended two-stage network DEA model for the biomass-biofuel logistics network design by Jae Dong Hong

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Automatic plant disease detection using computationally efficient convolutional neural network by Muhammad Rizwan, Samina Bibi, Sana Ul Haq, Muhammad Asif, Tariqullah Jan, Mohammad Haseeb Zafar

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Longitudinal evaluation of common and unique brain-networks in variants of primary progressive aphasia by Rajan Kashyap, Rose Dawn Bharath, Changsong Zhou, Kyrana Tsapkini, John E. Desmond, SH Annabel Chen, Kaviraja Udupa, PT Sivakumar, Sagarika Bhattacharjee

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Multiclass skin lesion classification and localziation from dermoscopic images using a novel network-level fused deep architecture and explainable artificial intelligence by Mehak Arshad, Muhammad Attique Khan, Nouf Abdullah Almujally, Areej Alasiry, Mehrez Marzougui, Yunyoung Nam

“…Traditional machine learning models require extensive feature engineering, which is time-consuming and less effective in handling complex data like skin lesions. This study proposes a deep learning-based network-level fusion architecture that integrates multiple deep models to enhance the classification and localization of skin lesions in dermoscopic images. …”
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Improving Disparity Consistency With Self-Refined Cost Volumes for Deep Learning-Based Satellite Stereo Matching by Jiyong Kim, Seoyeon Cho, Minkyung Chung, Yongil Kim

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Introducing a Deep Neural Network Model with Practical Implementation for Polyp Detection in Colonoscopy Videos by Hajar Keshavarz, Zohreh Ansari, Hossein Abootalebian, Babak Sabet, Mohammadreza Momenzadeh

“…Due to the lack of datasets with nonpolyp images, data collection was carried out. The proposed deep neural network structure was implemented on KVASIR-SEG and CVC-CLINIC datasets as polyp images in addition to the nonpolyp images extracted from the LDPolyp videos dataset. …”
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Computerized diagnosis of prostate cancer based on whole slide histology images and deep learning methods by V. A. Kovalev, D. M. Voynov, V. D. Malyshau, E. D. Lapo

“…The first solution is based on sequential analysis of image fragments and includes feature extraction using the ResNet50 network and the subsequent generalization of particular recognition results using a small convolutional network. …”
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Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings by David Verstraete, Andrés Ferrada, Enrique López Droguett, Viviana Meruane, Mohammad Modarres

“…To address this problem a deep learning enabled featureless methodology is proposed to automatically learn the features of the data. Time-frequency representations of the raw data are used to generate image representations of the raw signal, which are then fed into a deep convolutional neural network (CNN) architecture for classification and fault diagnosis. …”
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A New Classification Method in Ultrasound Images of Benign and Malignant Thyroid Nodules Based on Transfer Learning and Deep Convolutional Neural Network by Weibin Chen, Zhiyang Gu, Zhimin Liu, Yaoyao Fu, Zhipeng Ye, Xin Zhang, Lei Xiao

“…With data augmentation as a training set, transfer learning with the trained GoogLeNet convolutional neural network was performed to extract image features. …”
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Detection and classification of hypertensive retinopathy based on retinal image analysis using a deep learning approach by Bambang Krismono Triwijoyo, Ahmat Adil, Muhammad Zulfikri

“…Methods: This research utilizes secondary data, specifically a retinal image dataset from the open-source Messidor database. …”
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